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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 11 Dec 2013 14:10:33 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/11/t1386789094zxpysj3a8aab0y1.htm/, Retrieved Thu, 28 Mar 2024 16:13:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232142, Retrieved Thu, 28 Mar 2024 16:13:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact62
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Workshop 10 Parki...] [2013-12-11 19:10:33] [9e345f4af24c955bbdd99e7ffb840b0f] [Current]
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Dataseries X:
1 -4.813031 0.266482 119.992 157.302 74.997
1 -4.075192 0.33559 122.4 148.65 113.819
1 -4.443179 0.311173 116.682 131.111 111.555
1 -4.117501 0.334147 116.676 137.871 111.366
1 -3.747787 0.234513 116.014 141.781 110.655
1 -4.242867 0.299111 120.552 131.162 113.787
1 -5.634322 0.257682 120.267 137.244 114.82
1 -6.167603 0.183721 107.332 113.84 104.315
1 -5.498678 0.327769 95.73 132.068 91.754
1 -5.011879 0.325996 95.056 120.103 91.226
1 -5.24977 0.391002 88.333 112.24 84.072
1 -4.960234 0.363566 91.904 115.871 86.292
1 -6.547148 0.152813 136.926 159.866 131.276
1 -5.660217 0.254989 139.173 179.139 76.556
1 -6.105098 0.203653 152.845 163.305 75.836
1 -5.340115 0.210185 142.167 217.455 83.159
1 -5.44004 0.239764 144.188 349.259 82.764
1 -2.93107 0.434326 168.778 232.181 75.603
1 -3.949079 0.35787 153.046 175.829 68.623
1 -4.554466 0.340176 156.405 189.398 142.822
1 -4.095442 0.262564 153.848 165.738 65.782
1 -5.18696 0.237622 153.88 172.86 78.128
1 -4.330956 0.262384 167.93 193.221 79.068
1 -5.248776 0.210279 173.917 192.735 86.18
1 -5.557447 0.22089 163.656 200.841 76.779
1 -5.571843 0.236853 104.4 206.002 77.968
1 -6.18359 0.226278 171.041 208.313 75.501
1 -6.27169 0.196102 146.845 208.701 81.737
1 -7.120925 0.279789 155.358 227.383 80.055
1 -6.635729 0.209866 162.568 198.346 77.63
0 -7.3483 0.177551 197.076 206.896 192.055
0 -7.682587 0.173319 199.228 209.512 192.091
0 -7.067931 0.175181 198.383 215.203 193.104
0 -7.695734 0.17854 202.266 211.604 197.079
0 -7.964984 0.163519 203.184 211.526 196.16
0 -7.777685 0.170183 201.464 210.565 195.708
1 -6.149653 0.218037 177.876 192.921 168.013
1 -6.006414 0.196371 176.17 185.604 163.564
1 -6.452058 0.212294 180.198 201.249 175.456
1 -6.006647 0.266892 187.733 202.324 173.015
1 -6.647379 0.201095 186.163 197.724 177.584
1 -7.044105 0.063412 184.055 196.537 166.977
0 -7.31055 0.098648 237.226 247.326 225.227
0 -6.793547 0.158266 241.404 248.834 232.483
0 -7.057869 0.091608 243.439 250.912 232.435
0 -6.99582 0.102083 242.852 255.034 227.911
0 -7.156076 0.127642 245.51 262.09 231.848
0 -7.31951 0.200873 252.455 261.487 182.786
0 -6.439398 0.266392 122.188 128.611 115.765
0 -6.482096 0.264967 122.964 130.049 114.676
0 -6.650471 0.254498 124.445 135.069 117.495
0 -6.689151 0.291954 126.344 134.231 112.773
0 -7.072419 0.220434 128.001 138.052 122.08
0 -6.836811 0.269866 129.336 139.867 118.604
1 -4.649573 0.205558 108.807 134.656 102.874
1 -4.333543 0.221727 109.86 126.358 104.437
1 -4.438453 0.238298 110.417 131.067 103.37
1 -4.60826 0.290024 117.274 129.916 110.402
1 -4.476755 0.262633 116.879 131.897 108.153
1 -4.609161 0.221711 114.847 271.314 104.68
0 -7.040508 0.066994 209.144 237.494 109.379
0 -7.293801 0.086372 223.365 238.987 98.664
0 -6.966321 0.095882 222.236 231.345 205.495
0 -7.24562 0.018689 228.832 234.619 223.634
0 -7.496264 0.056844 229.401 252.221 221.156
0 -7.314237 0.006274 228.969 239.541 113.201
1 -5.409423 0.22685 140.341 159.774 67.021
1 -5.324574 0.20566 136.969 166.607 66.004
1 -5.86975 0.151814 143.533 162.215 65.809
1 -6.261141 0.120956 148.09 162.824 67.343
1 -5.720868 0.15883 142.729 162.408 65.476
1 -5.207985 0.224852 136.358 176.595 65.75
1 -5.79182 0.329066 120.08 139.71 111.208
1 -5.389129 0.306636 112.014 588.518 107.024
1 -5.31336 0.201861 110.793 128.101 107.316
1 -5.477592 0.315074 110.707 122.611 105.007
1 -5.775966 0.341169 112.876 148.826 106.981
1 -5.391029 0.250572 110.568 125.394 106.821
1 -5.115212 0.249494 95.385 102.145 90.264
1 -4.913885 0.265699 100.77 115.697 85.545
1 -4.441519 0.155097 96.106 108.664 84.51
1 -5.132032 0.210458 95.605 107.715 87.549
1 -5.022288 0.146948 100.96 110.019 95.628
1 -6.025367 0.078202 98.804 102.305 87.804
1 -5.288912 0.343073 176.858 205.56 75.344
1 -5.657899 0.315903 180.978 200.125 155.495
1 -6.366916 0.335753 178.222 202.45 141.047
1 -5.515071 0.299549 176.281 227.381 125.61
1 -5.783272 0.299793 173.898 211.35 74.677
1 -4.379411 0.375531 179.711 225.93 144.878
1 -4.508984 0.389232 166.605 206.008 78.032
1 -6.411497 0.207156 151.955 163.335 147.226
1 -5.952058 0.08784 148.272 164.989 142.299
1 -6.152551 0.17352 152.125 161.469 76.596
1 -6.251425 0.188056 157.821 172.975 68.401
1 -6.247076 0.180528 157.447 163.267 149.605
1 -6.41744 0.194627 159.116 168.913 144.811
1 -4.020042 0.265315 125.036 143.946 116.187
1 -5.159169 0.202146 125.791 140.557 96.206
1 -3.760348 0.242861 126.512 141.756 99.77
1 -3.700544 0.260481 125.641 141.068 116.346
1 -4.20273 0.310163 128.451 150.449 75.632
1 -3.269487 0.270641 139.224 586.567 66.157
1 -6.878393 0.089267 150.258 154.609 75.349
1 -7.111576 0.14478 154.003 160.267 128.621
1 -6.997403 0.210279 149.689 160.368 133.608
1 -6.981201 0.18455 155.078 163.736 144.148
1 -6.600023 0.249172 151.884 157.765 133.751
1 -6.739151 0.160686 151.989 157.339 132.857
1 -5.845099 0.278679 193.03 208.9 80.297
1 -5.25832 0.256454 200.714 223.982 89.686
1 -6.471427 0.184378 208.519 220.315 199.02
1 -4.876336 0.212054 204.664 221.3 189.621
1 -5.96304 0.250283 210.141 232.706 185.258
1 -6.729713 0.181701 206.327 226.355 92.02
1 -4.673241 0.261549 151.872 492.892 69.085
1 -6.051233 0.27328 158.219 442.557 71.948
1 -4.597834 0.372114 170.756 450.247 79.032
1 -4.913137 0.393056 178.285 442.824 82.063
1 -5.517173 0.389295 217.116 233.481 93.978
1 -6.186128 0.279933 128.94 479.697 88.251
1 -4.711007 0.281618 176.824 215.293 83.961
1 -5.418787 0.160267 138.19 203.522 83.34
1 -5.44514 0.142466 182.018 197.173 79.187
1 -5.944191 0.143359 156.239 195.107 79.82
1 -5.594275 0.12795 145.174 198.109 80.637
1 -5.540351 0.087165 138.145 197.238 81.114
1 -5.825257 0.115697 166.888 198.966 79.512
1 -6.890021 0.152941 119.031 127.533 109.216
1 -5.892061 0.195976 120.078 126.632 105.667
1 -6.135296 0.20363 120.289 128.143 100.209
1 -6.112667 0.217013 120.256 125.306 104.773
1 -5.436135 0.254909 119.056 125.213 86.795
1 -6.448134 0.178713 118.747 123.723 109.836
1 -5.301321 0.320385 106.516 112.777 93.105
1 -5.333619 0.322044 110.453 127.611 105.554
1 -4.378916 0.300067 113.4 133.344 107.816
1 -4.654894 0.304107 113.166 130.27 100.673
1 -5.634576 0.306014 112.239 126.609 104.095
1 -5.866357 0.23307 116.15 131.731 109.815
1 -4.796845 0.397749 170.368 268.796 79.543
1 -5.410336 0.288917 208.083 253.792 91.802
1 -5.585259 0.310746 198.458 219.29 148.691
1 -5.898673 0.213353 202.805 231.508 86.232
1 -6.132663 0.220617 202.544 241.35 164.168
1 -5.456811 0.345238 223.361 263.872 87.638
1 -3.297668 0.414758 169.774 191.759 151.451
1 -4.276605 0.355736 183.52 216.814 161.34
1 -3.377325 0.335357 188.62 216.302 165.982
1 -4.892495 0.262281 202.632 565.74 177.258
1 -4.484303 0.340256 186.695 211.961 149.442
1 -2.434031 0.450493 192.818 224.429 168.793
1 -2.839756 0.356224 198.116 233.099 174.478
1 -4.865194 0.246404 121.345 139.644 98.25
1 -4.239028 0.175691 119.1 128.442 88.833
1 -3.583722 0.207914 117.87 127.349 95.654
1 -5.4351 0.230532 122.336 142.369 94.794
1 -3.444478 0.303214 117.963 134.209 100.757
1 -5.070096 0.280091 126.144 154.284 97.543
1 -5.498456 0.234196 127.93 138.752 112.173
1 -5.185987 0.259229 114.238 124.393 77.022
1 -5.283009 0.226528 115.322 135.738 107.802
1 -5.529833 0.24275 114.554 126.778 91.121
1 -5.617124 0.184896 112.15 131.669 97.527
1 -2.929379 0.396746 102.273 142.83 85.902
0 -6.816086 0.17227 236.2 244.663 102.137
0 -7.018057 0.176316 237.323 243.709 229.256
0 -7.517934 0.160414 260.105 264.919 237.303
0 -5.736781 0.164529 197.569 217.627 90.794
0 -7.169701 0.073298 240.301 245.135 219.783
0 -7.3045 0.171088 244.99 272.21 239.17
0 -6.323531 0.218885 112.547 133.374 105.715
0 -6.085567 0.192375 110.739 113.597 100.139
0 -5.943501 0.19215 113.715 116.443 96.913
0 -6.012559 0.229298 117.004 144.466 99.923
0 -5.966779 0.197938 115.38 123.109 108.634
0 -6.016891 0.109256 116.388 129.038 108.97
1 -6.486822 0.197919 151.737 190.204 129.859
1 -6.311987 0.182459 148.79 158.359 138.99
1 -5.711205 0.240875 148.143 155.982 135.041
1 -6.261446 0.183218 150.44 163.441 144.736
1 -5.704053 0.216204 148.462 161.078 141.998
1 -6.27717 0.109397 149.818 163.417 144.786
0 -5.61907 0.191576 117.226 123.925 106.656
0 -5.198864 0.206768 116.848 217.552 99.503
0 -5.592584 0.133917 116.286 177.291 96.983
0 -6.431119 0.15331 116.556 592.03 86.228
0 -6.359018 0.116636 116.342 581.289 94.246
0 -6.710219 0.149694 114.563 119.167 86.647
0 -6.934474 0.15989 201.774 262.707 78.228
0 -6.538586 0.121952 174.188 230.978 94.261
0 -6.195325 0.129303 209.516 253.017 89.488
0 -6.787197 0.158453 174.688 240.005 74.287
0 -6.744577 0.207454 198.764 396.961 74.904
0 -5.724056 0.190667 214.289 260.277 77.973
 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time19 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 19 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]19 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time19 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Multiple Linear Regression - Estimated Regression Equation
status[t] = + 1.74908 + 0.144583spread1[t] + 0.851073spread2[t] -0.000639428`MDVP:Fo(Hz)`[t] -0.000473352`MDVP:Fhi(Hz)`[t] -0.00149778`MDVP:Flo(Hz)`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  1.74908 +  0.144583spread1[t] +  0.851073spread2[t] -0.000639428`MDVP:Fo(Hz)`[t] -0.000473352`MDVP:Fhi(Hz)`[t] -0.00149778`MDVP:Flo(Hz)`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  1.74908 +  0.144583spread1[t] +  0.851073spread2[t] -0.000639428`MDVP:Fo(Hz)`[t] -0.000473352`MDVP:Fhi(Hz)`[t] -0.00149778`MDVP:Flo(Hz)`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
status[t] = + 1.74908 + 0.144583spread1[t] + 0.851073spread2[t] -0.000639428`MDVP:Fo(Hz)`[t] -0.000473352`MDVP:Fhi(Hz)`[t] -0.00149778`MDVP:Flo(Hz)`[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.749080.2427547.2051.34317e-116.71586e-12
spread10.1445830.03233384.4721.33729e-056.68643e-06
spread20.8510730.3926042.1680.0314270.0157135
`MDVP:Fo(Hz)`-0.0006394280.000855705-0.74730.4558390.22792
`MDVP:Fhi(Hz)`-0.0004733520.000303402-1.560.1203980.060199
`MDVP:Flo(Hz)`-0.001497780.000738065-2.0290.04382680.0219134

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 1.74908 & 0.242754 & 7.205 & 1.34317e-11 & 6.71586e-12 \tabularnewline
spread1 & 0.144583 & 0.0323338 & 4.472 & 1.33729e-05 & 6.68643e-06 \tabularnewline
spread2 & 0.851073 & 0.392604 & 2.168 & 0.031427 & 0.0157135 \tabularnewline
`MDVP:Fo(Hz)` & -0.000639428 & 0.000855705 & -0.7473 & 0.455839 & 0.22792 \tabularnewline
`MDVP:Fhi(Hz)` & -0.000473352 & 0.000303402 & -1.56 & 0.120398 & 0.060199 \tabularnewline
`MDVP:Flo(Hz)` & -0.00149778 & 0.000738065 & -2.029 & 0.0438268 & 0.0219134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]1.74908[/C][C]0.242754[/C][C]7.205[/C][C]1.34317e-11[/C][C]6.71586e-12[/C][/ROW]
[ROW][C]spread1[/C][C]0.144583[/C][C]0.0323338[/C][C]4.472[/C][C]1.33729e-05[/C][C]6.68643e-06[/C][/ROW]
[ROW][C]spread2[/C][C]0.851073[/C][C]0.392604[/C][C]2.168[/C][C]0.031427[/C][C]0.0157135[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.000639428[/C][C]0.000855705[/C][C]-0.7473[/C][C]0.455839[/C][C]0.22792[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]-0.000473352[/C][C]0.000303402[/C][C]-1.56[/C][C]0.120398[/C][C]0.060199[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.00149778[/C][C]0.000738065[/C][C]-2.029[/C][C]0.0438268[/C][C]0.0219134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.749080.2427547.2051.34317e-116.71586e-12
spread10.1445830.03233384.4721.33729e-056.68643e-06
spread20.8510730.3926042.1680.0314270.0157135
`MDVP:Fo(Hz)`-0.0006394280.000855705-0.74730.4558390.22792
`MDVP:Fhi(Hz)`-0.0004733520.000303402-1.560.1203980.060199
`MDVP:Flo(Hz)`-0.001497780.000738065-2.0290.04382680.0219134







Multiple Linear Regression - Regression Statistics
Multiple R0.615191
R-squared0.37846
Adjusted R-squared0.362017
F-TEST (value)23.0167
F-TEST (DF numerator)5
F-TEST (DF denominator)189
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.344958
Sum Squared Residuals22.4902

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.615191 \tabularnewline
R-squared & 0.37846 \tabularnewline
Adjusted R-squared & 0.362017 \tabularnewline
F-TEST (value) & 23.0167 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 189 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.344958 \tabularnewline
Sum Squared Residuals & 22.4902 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.615191[/C][/ROW]
[ROW][C]R-squared[/C][C]0.37846[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.362017[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]23.0167[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]189[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.344958[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]22.4902[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.615191
R-squared0.37846
Adjusted R-squared0.362017
F-TEST (value)23.0167
F-TEST (DF numerator)5
F-TEST (DF denominator)189
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.344958
Sum Squared Residuals22.4902







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111.01648-0.0164817
211.12639-0.126385
311.06775-0.0677493
411.13148-0.131476
511.09977-0.0997721
611.0806-0.0806036
710.839920.16008
810.7349550.265045
910.9718690.0281312
1011.04763-0.047628
1111.08729-0.0872939
1211.09848-0.0984785
1310.5726830.427317
1410.8592750.140725
1510.7510940.248906
1610.8374840.162516
1710.785120.21488
1811.36388-0.363881
1911.19881-0.198813
2010.9765210.0234785
2111.10506-0.105058
2210.9041330.0958668
2311.02894-0.0289409
2410.8376450.162355
2510.8188520.181148
2610.8640220.135978
2710.7265630.273437
2810.6940910.305909
2910.6307630.369237
3010.6541710.345829
3100.326147-0.326147
3200.271545-0.271545
3300.358327-0.358327
3400.263684-0.263684
3500.212797-0.212797
3600.247781-0.247781
3710.5888090.411191
3810.6022970.397703
3910.5236240.476376
4010.6328180.367182
4110.480520.51948
4210.3237780.676222
4300.169958-0.169958
4400.281193-0.281193
4500.184033-0.184033
4600.207119-0.207119
4700.194765-0.194765
4800.302789-0.302789
4900.732376-0.732376
5000.725444-0.725444
5100.684645-0.684645
5200.717185-0.717185
5300.584094-0.584094
5400.663723-0.663723
5510.9643820.035618
5611.02475-0.024749
5711.0227-0.0226969
5811.0278-0.0277962
5911.02618-0.0261812
6010.9127180.0872823
6100.378186-0.378186
6200.364305-0.364305
6300.264077-0.264077
6400.125063-0.125063
6500.116312-0.116312
6600.267563-0.267563
6710.8942880.105712
6810.8889670.111033
6910.7624910.237509
7010.674140.32586
7110.7909090.209091
7210.9182010.0817993
7310.8822640.117736
7410.7203770.279623
7510.8604430.139557
7610.9391630.0608372
7710.9014790.0985206
7810.8928370.107163
7910.977310.02269
8011.01742-0.0174199
8110.9994470.000553014
8210.9429450.0570551
8310.8881450.111855
8410.7013580.298642
8510.9531380.0468624
8610.7565540.243446
8710.6932380.306762
8810.7981490.201851
8910.8449780.155022
9010.9966470.00335342
9111.1075-0.107504
9210.6034040.396596
9310.5772360.422764
9410.7187790.281221
9510.720040.27996
9610.5974710.402529
9710.5882790.411721
9811.07154-0.0715441
9910.8841330.115867
10011.11466-0.114663
10111.11436-0.114361
10211.13878-0.13878
10311.04094-0.0409401
10410.5484380.451562
10510.4771070.522893
10610.54460.4554
10710.5042180.495782
10810.6347690.365231
10910.5408190.459181
11010.7985780.201422
11110.8383860.161614
11210.4346370.565363
11310.704890.29511
11410.5779410.422059
11510.553820.44618
11610.8621120.137888
11710.6883420.311658
11810.9603260.0396738
11910.9267220.0732783
12010.8926050.107395
12110.6512240.348776
12210.9668980.0331019
12310.7924930.207507
12410.7547330.245267
12510.6998530.300147
12610.7417610.258239
12710.7190390.280961
12810.6853320.314668
12910.5830070.416993
13010.7689930.231007
13110.7476640.252336
13210.7568540.243146
13310.9146590.0853407
13410.6698860.330114
13510.994330.00567006
13610.9628870.0371129
13711.07423-0.0742304
13811.05007-0.0500705
13910.9072490.0927512
14010.7981640.201836
14111.03874-0.0387429
14210.8220440.177956
14310.752610.24739
14410.7093940.290606
14510.5605220.439478
14610.8549540.145046
14711.19912-0.199117
14810.9718870.0281134
14911.07459-0.0745914
15010.6020750.397925
15110.946770.0532299
15211.29822-0.298223
15311.14333-0.143326
15410.9645170.0354826
15511.01571-0.0157108
15611.12897-0.128968
15710.8718630.128137
15811.21926-0.219258
15910.9546230.0453774
16010.8379270.162073
16110.972610.0273903
16210.8785860.121414
16310.8864230.113577
16410.8141910.185809
16511.40154-0.401536
16600.490385-0.490385
16700.273964-0.273964
16800.151496-0.151496
16900.694334-0.694334
17000.175972-0.175972
17100.194857-0.194857
17200.727659-0.727659
17300.758372-0.758372
17400.780302-0.780302
17500.782057-0.782057
17600.760087-0.760087
17700.673413-0.673413
17810.5980840.401916
17910.6134870.386513
18010.7575190.242481
18110.6093730.390627
18210.724520.27548
18310.5446070.455393
18400.806341-0.806341
18500.846662-0.846662
18600.750927-0.750927
18700.465813-0.465813
18800.438237-0.438237
18900.64686-0.64686
19000.512014-0.512014
19100.545608-0.545608
19200.575621-0.575621
19300.566053-0.566053
19400.523304-0.523304
19500.706742-0.706742

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 1.01648 & -0.0164817 \tabularnewline
2 & 1 & 1.12639 & -0.126385 \tabularnewline
3 & 1 & 1.06775 & -0.0677493 \tabularnewline
4 & 1 & 1.13148 & -0.131476 \tabularnewline
5 & 1 & 1.09977 & -0.0997721 \tabularnewline
6 & 1 & 1.0806 & -0.0806036 \tabularnewline
7 & 1 & 0.83992 & 0.16008 \tabularnewline
8 & 1 & 0.734955 & 0.265045 \tabularnewline
9 & 1 & 0.971869 & 0.0281312 \tabularnewline
10 & 1 & 1.04763 & -0.047628 \tabularnewline
11 & 1 & 1.08729 & -0.0872939 \tabularnewline
12 & 1 & 1.09848 & -0.0984785 \tabularnewline
13 & 1 & 0.572683 & 0.427317 \tabularnewline
14 & 1 & 0.859275 & 0.140725 \tabularnewline
15 & 1 & 0.751094 & 0.248906 \tabularnewline
16 & 1 & 0.837484 & 0.162516 \tabularnewline
17 & 1 & 0.78512 & 0.21488 \tabularnewline
18 & 1 & 1.36388 & -0.363881 \tabularnewline
19 & 1 & 1.19881 & -0.198813 \tabularnewline
20 & 1 & 0.976521 & 0.0234785 \tabularnewline
21 & 1 & 1.10506 & -0.105058 \tabularnewline
22 & 1 & 0.904133 & 0.0958668 \tabularnewline
23 & 1 & 1.02894 & -0.0289409 \tabularnewline
24 & 1 & 0.837645 & 0.162355 \tabularnewline
25 & 1 & 0.818852 & 0.181148 \tabularnewline
26 & 1 & 0.864022 & 0.135978 \tabularnewline
27 & 1 & 0.726563 & 0.273437 \tabularnewline
28 & 1 & 0.694091 & 0.305909 \tabularnewline
29 & 1 & 0.630763 & 0.369237 \tabularnewline
30 & 1 & 0.654171 & 0.345829 \tabularnewline
31 & 0 & 0.326147 & -0.326147 \tabularnewline
32 & 0 & 0.271545 & -0.271545 \tabularnewline
33 & 0 & 0.358327 & -0.358327 \tabularnewline
34 & 0 & 0.263684 & -0.263684 \tabularnewline
35 & 0 & 0.212797 & -0.212797 \tabularnewline
36 & 0 & 0.247781 & -0.247781 \tabularnewline
37 & 1 & 0.588809 & 0.411191 \tabularnewline
38 & 1 & 0.602297 & 0.397703 \tabularnewline
39 & 1 & 0.523624 & 0.476376 \tabularnewline
40 & 1 & 0.632818 & 0.367182 \tabularnewline
41 & 1 & 0.48052 & 0.51948 \tabularnewline
42 & 1 & 0.323778 & 0.676222 \tabularnewline
43 & 0 & 0.169958 & -0.169958 \tabularnewline
44 & 0 & 0.281193 & -0.281193 \tabularnewline
45 & 0 & 0.184033 & -0.184033 \tabularnewline
46 & 0 & 0.207119 & -0.207119 \tabularnewline
47 & 0 & 0.194765 & -0.194765 \tabularnewline
48 & 0 & 0.302789 & -0.302789 \tabularnewline
49 & 0 & 0.732376 & -0.732376 \tabularnewline
50 & 0 & 0.725444 & -0.725444 \tabularnewline
51 & 0 & 0.684645 & -0.684645 \tabularnewline
52 & 0 & 0.717185 & -0.717185 \tabularnewline
53 & 0 & 0.584094 & -0.584094 \tabularnewline
54 & 0 & 0.663723 & -0.663723 \tabularnewline
55 & 1 & 0.964382 & 0.035618 \tabularnewline
56 & 1 & 1.02475 & -0.024749 \tabularnewline
57 & 1 & 1.0227 & -0.0226969 \tabularnewline
58 & 1 & 1.0278 & -0.0277962 \tabularnewline
59 & 1 & 1.02618 & -0.0261812 \tabularnewline
60 & 1 & 0.912718 & 0.0872823 \tabularnewline
61 & 0 & 0.378186 & -0.378186 \tabularnewline
62 & 0 & 0.364305 & -0.364305 \tabularnewline
63 & 0 & 0.264077 & -0.264077 \tabularnewline
64 & 0 & 0.125063 & -0.125063 \tabularnewline
65 & 0 & 0.116312 & -0.116312 \tabularnewline
66 & 0 & 0.267563 & -0.267563 \tabularnewline
67 & 1 & 0.894288 & 0.105712 \tabularnewline
68 & 1 & 0.888967 & 0.111033 \tabularnewline
69 & 1 & 0.762491 & 0.237509 \tabularnewline
70 & 1 & 0.67414 & 0.32586 \tabularnewline
71 & 1 & 0.790909 & 0.209091 \tabularnewline
72 & 1 & 0.918201 & 0.0817993 \tabularnewline
73 & 1 & 0.882264 & 0.117736 \tabularnewline
74 & 1 & 0.720377 & 0.279623 \tabularnewline
75 & 1 & 0.860443 & 0.139557 \tabularnewline
76 & 1 & 0.939163 & 0.0608372 \tabularnewline
77 & 1 & 0.901479 & 0.0985206 \tabularnewline
78 & 1 & 0.892837 & 0.107163 \tabularnewline
79 & 1 & 0.97731 & 0.02269 \tabularnewline
80 & 1 & 1.01742 & -0.0174199 \tabularnewline
81 & 1 & 0.999447 & 0.000553014 \tabularnewline
82 & 1 & 0.942945 & 0.0570551 \tabularnewline
83 & 1 & 0.888145 & 0.111855 \tabularnewline
84 & 1 & 0.701358 & 0.298642 \tabularnewline
85 & 1 & 0.953138 & 0.0468624 \tabularnewline
86 & 1 & 0.756554 & 0.243446 \tabularnewline
87 & 1 & 0.693238 & 0.306762 \tabularnewline
88 & 1 & 0.798149 & 0.201851 \tabularnewline
89 & 1 & 0.844978 & 0.155022 \tabularnewline
90 & 1 & 0.996647 & 0.00335342 \tabularnewline
91 & 1 & 1.1075 & -0.107504 \tabularnewline
92 & 1 & 0.603404 & 0.396596 \tabularnewline
93 & 1 & 0.577236 & 0.422764 \tabularnewline
94 & 1 & 0.718779 & 0.281221 \tabularnewline
95 & 1 & 0.72004 & 0.27996 \tabularnewline
96 & 1 & 0.597471 & 0.402529 \tabularnewline
97 & 1 & 0.588279 & 0.411721 \tabularnewline
98 & 1 & 1.07154 & -0.0715441 \tabularnewline
99 & 1 & 0.884133 & 0.115867 \tabularnewline
100 & 1 & 1.11466 & -0.114663 \tabularnewline
101 & 1 & 1.11436 & -0.114361 \tabularnewline
102 & 1 & 1.13878 & -0.13878 \tabularnewline
103 & 1 & 1.04094 & -0.0409401 \tabularnewline
104 & 1 & 0.548438 & 0.451562 \tabularnewline
105 & 1 & 0.477107 & 0.522893 \tabularnewline
106 & 1 & 0.5446 & 0.4554 \tabularnewline
107 & 1 & 0.504218 & 0.495782 \tabularnewline
108 & 1 & 0.634769 & 0.365231 \tabularnewline
109 & 1 & 0.540819 & 0.459181 \tabularnewline
110 & 1 & 0.798578 & 0.201422 \tabularnewline
111 & 1 & 0.838386 & 0.161614 \tabularnewline
112 & 1 & 0.434637 & 0.565363 \tabularnewline
113 & 1 & 0.70489 & 0.29511 \tabularnewline
114 & 1 & 0.577941 & 0.422059 \tabularnewline
115 & 1 & 0.55382 & 0.44618 \tabularnewline
116 & 1 & 0.862112 & 0.137888 \tabularnewline
117 & 1 & 0.688342 & 0.311658 \tabularnewline
118 & 1 & 0.960326 & 0.0396738 \tabularnewline
119 & 1 & 0.926722 & 0.0732783 \tabularnewline
120 & 1 & 0.892605 & 0.107395 \tabularnewline
121 & 1 & 0.651224 & 0.348776 \tabularnewline
122 & 1 & 0.966898 & 0.0331019 \tabularnewline
123 & 1 & 0.792493 & 0.207507 \tabularnewline
124 & 1 & 0.754733 & 0.245267 \tabularnewline
125 & 1 & 0.699853 & 0.300147 \tabularnewline
126 & 1 & 0.741761 & 0.258239 \tabularnewline
127 & 1 & 0.719039 & 0.280961 \tabularnewline
128 & 1 & 0.685332 & 0.314668 \tabularnewline
129 & 1 & 0.583007 & 0.416993 \tabularnewline
130 & 1 & 0.768993 & 0.231007 \tabularnewline
131 & 1 & 0.747664 & 0.252336 \tabularnewline
132 & 1 & 0.756854 & 0.243146 \tabularnewline
133 & 1 & 0.914659 & 0.0853407 \tabularnewline
134 & 1 & 0.669886 & 0.330114 \tabularnewline
135 & 1 & 0.99433 & 0.00567006 \tabularnewline
136 & 1 & 0.962887 & 0.0371129 \tabularnewline
137 & 1 & 1.07423 & -0.0742304 \tabularnewline
138 & 1 & 1.05007 & -0.0500705 \tabularnewline
139 & 1 & 0.907249 & 0.0927512 \tabularnewline
140 & 1 & 0.798164 & 0.201836 \tabularnewline
141 & 1 & 1.03874 & -0.0387429 \tabularnewline
142 & 1 & 0.822044 & 0.177956 \tabularnewline
143 & 1 & 0.75261 & 0.24739 \tabularnewline
144 & 1 & 0.709394 & 0.290606 \tabularnewline
145 & 1 & 0.560522 & 0.439478 \tabularnewline
146 & 1 & 0.854954 & 0.145046 \tabularnewline
147 & 1 & 1.19912 & -0.199117 \tabularnewline
148 & 1 & 0.971887 & 0.0281134 \tabularnewline
149 & 1 & 1.07459 & -0.0745914 \tabularnewline
150 & 1 & 0.602075 & 0.397925 \tabularnewline
151 & 1 & 0.94677 & 0.0532299 \tabularnewline
152 & 1 & 1.29822 & -0.298223 \tabularnewline
153 & 1 & 1.14333 & -0.143326 \tabularnewline
154 & 1 & 0.964517 & 0.0354826 \tabularnewline
155 & 1 & 1.01571 & -0.0157108 \tabularnewline
156 & 1 & 1.12897 & -0.128968 \tabularnewline
157 & 1 & 0.871863 & 0.128137 \tabularnewline
158 & 1 & 1.21926 & -0.219258 \tabularnewline
159 & 1 & 0.954623 & 0.0453774 \tabularnewline
160 & 1 & 0.837927 & 0.162073 \tabularnewline
161 & 1 & 0.97261 & 0.0273903 \tabularnewline
162 & 1 & 0.878586 & 0.121414 \tabularnewline
163 & 1 & 0.886423 & 0.113577 \tabularnewline
164 & 1 & 0.814191 & 0.185809 \tabularnewline
165 & 1 & 1.40154 & -0.401536 \tabularnewline
166 & 0 & 0.490385 & -0.490385 \tabularnewline
167 & 0 & 0.273964 & -0.273964 \tabularnewline
168 & 0 & 0.151496 & -0.151496 \tabularnewline
169 & 0 & 0.694334 & -0.694334 \tabularnewline
170 & 0 & 0.175972 & -0.175972 \tabularnewline
171 & 0 & 0.194857 & -0.194857 \tabularnewline
172 & 0 & 0.727659 & -0.727659 \tabularnewline
173 & 0 & 0.758372 & -0.758372 \tabularnewline
174 & 0 & 0.780302 & -0.780302 \tabularnewline
175 & 0 & 0.782057 & -0.782057 \tabularnewline
176 & 0 & 0.760087 & -0.760087 \tabularnewline
177 & 0 & 0.673413 & -0.673413 \tabularnewline
178 & 1 & 0.598084 & 0.401916 \tabularnewline
179 & 1 & 0.613487 & 0.386513 \tabularnewline
180 & 1 & 0.757519 & 0.242481 \tabularnewline
181 & 1 & 0.609373 & 0.390627 \tabularnewline
182 & 1 & 0.72452 & 0.27548 \tabularnewline
183 & 1 & 0.544607 & 0.455393 \tabularnewline
184 & 0 & 0.806341 & -0.806341 \tabularnewline
185 & 0 & 0.846662 & -0.846662 \tabularnewline
186 & 0 & 0.750927 & -0.750927 \tabularnewline
187 & 0 & 0.465813 & -0.465813 \tabularnewline
188 & 0 & 0.438237 & -0.438237 \tabularnewline
189 & 0 & 0.64686 & -0.64686 \tabularnewline
190 & 0 & 0.512014 & -0.512014 \tabularnewline
191 & 0 & 0.545608 & -0.545608 \tabularnewline
192 & 0 & 0.575621 & -0.575621 \tabularnewline
193 & 0 & 0.566053 & -0.566053 \tabularnewline
194 & 0 & 0.523304 & -0.523304 \tabularnewline
195 & 0 & 0.706742 & -0.706742 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]1.01648[/C][C]-0.0164817[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]1.12639[/C][C]-0.126385[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]1.06775[/C][C]-0.0677493[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]1.13148[/C][C]-0.131476[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]1.09977[/C][C]-0.0997721[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]1.0806[/C][C]-0.0806036[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.83992[/C][C]0.16008[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.734955[/C][C]0.265045[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.971869[/C][C]0.0281312[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]1.04763[/C][C]-0.047628[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]1.08729[/C][C]-0.0872939[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]1.09848[/C][C]-0.0984785[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.572683[/C][C]0.427317[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.859275[/C][C]0.140725[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.751094[/C][C]0.248906[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.837484[/C][C]0.162516[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.78512[/C][C]0.21488[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]1.36388[/C][C]-0.363881[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.19881[/C][C]-0.198813[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.976521[/C][C]0.0234785[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]1.10506[/C][C]-0.105058[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.904133[/C][C]0.0958668[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]1.02894[/C][C]-0.0289409[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.837645[/C][C]0.162355[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.818852[/C][C]0.181148[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.864022[/C][C]0.135978[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.726563[/C][C]0.273437[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.694091[/C][C]0.305909[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.630763[/C][C]0.369237[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.654171[/C][C]0.345829[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.326147[/C][C]-0.326147[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.271545[/C][C]-0.271545[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.358327[/C][C]-0.358327[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.263684[/C][C]-0.263684[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.212797[/C][C]-0.212797[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.247781[/C][C]-0.247781[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.588809[/C][C]0.411191[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.602297[/C][C]0.397703[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.523624[/C][C]0.476376[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.632818[/C][C]0.367182[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.48052[/C][C]0.51948[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.323778[/C][C]0.676222[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.169958[/C][C]-0.169958[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.281193[/C][C]-0.281193[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.184033[/C][C]-0.184033[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.207119[/C][C]-0.207119[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.194765[/C][C]-0.194765[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0.302789[/C][C]-0.302789[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.732376[/C][C]-0.732376[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.725444[/C][C]-0.725444[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.684645[/C][C]-0.684645[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.717185[/C][C]-0.717185[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.584094[/C][C]-0.584094[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.663723[/C][C]-0.663723[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.964382[/C][C]0.035618[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]1.02475[/C][C]-0.024749[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]1.0227[/C][C]-0.0226969[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]1.0278[/C][C]-0.0277962[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]1.02618[/C][C]-0.0261812[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.912718[/C][C]0.0872823[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.378186[/C][C]-0.378186[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.364305[/C][C]-0.364305[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.264077[/C][C]-0.264077[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.125063[/C][C]-0.125063[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.116312[/C][C]-0.116312[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.267563[/C][C]-0.267563[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.894288[/C][C]0.105712[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.888967[/C][C]0.111033[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.762491[/C][C]0.237509[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.67414[/C][C]0.32586[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.790909[/C][C]0.209091[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]0.918201[/C][C]0.0817993[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.882264[/C][C]0.117736[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.720377[/C][C]0.279623[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.860443[/C][C]0.139557[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.939163[/C][C]0.0608372[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.901479[/C][C]0.0985206[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.892837[/C][C]0.107163[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.97731[/C][C]0.02269[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]1.01742[/C][C]-0.0174199[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]0.999447[/C][C]0.000553014[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]0.942945[/C][C]0.0570551[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.888145[/C][C]0.111855[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.701358[/C][C]0.298642[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.953138[/C][C]0.0468624[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.756554[/C][C]0.243446[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.693238[/C][C]0.306762[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.798149[/C][C]0.201851[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]0.844978[/C][C]0.155022[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.996647[/C][C]0.00335342[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.1075[/C][C]-0.107504[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.603404[/C][C]0.396596[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.577236[/C][C]0.422764[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.718779[/C][C]0.281221[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.72004[/C][C]0.27996[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.597471[/C][C]0.402529[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.588279[/C][C]0.411721[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]1.07154[/C][C]-0.0715441[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.884133[/C][C]0.115867[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]1.11466[/C][C]-0.114663[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.11436[/C][C]-0.114361[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.13878[/C][C]-0.13878[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]1.04094[/C][C]-0.0409401[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.548438[/C][C]0.451562[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.477107[/C][C]0.522893[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.5446[/C][C]0.4554[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.504218[/C][C]0.495782[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.634769[/C][C]0.365231[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.540819[/C][C]0.459181[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.798578[/C][C]0.201422[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.838386[/C][C]0.161614[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.434637[/C][C]0.565363[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.70489[/C][C]0.29511[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.577941[/C][C]0.422059[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.55382[/C][C]0.44618[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.862112[/C][C]0.137888[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.688342[/C][C]0.311658[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.960326[/C][C]0.0396738[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.926722[/C][C]0.0732783[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.892605[/C][C]0.107395[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.651224[/C][C]0.348776[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.966898[/C][C]0.0331019[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.792493[/C][C]0.207507[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.754733[/C][C]0.245267[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.699853[/C][C]0.300147[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.741761[/C][C]0.258239[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.719039[/C][C]0.280961[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.685332[/C][C]0.314668[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.583007[/C][C]0.416993[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.768993[/C][C]0.231007[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.747664[/C][C]0.252336[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.756854[/C][C]0.243146[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.914659[/C][C]0.0853407[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.669886[/C][C]0.330114[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.99433[/C][C]0.00567006[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.962887[/C][C]0.0371129[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.07423[/C][C]-0.0742304[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.05007[/C][C]-0.0500705[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.907249[/C][C]0.0927512[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.798164[/C][C]0.201836[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]1.03874[/C][C]-0.0387429[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.822044[/C][C]0.177956[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.75261[/C][C]0.24739[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.709394[/C][C]0.290606[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.560522[/C][C]0.439478[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.854954[/C][C]0.145046[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.19912[/C][C]-0.199117[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.971887[/C][C]0.0281134[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.07459[/C][C]-0.0745914[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.602075[/C][C]0.397925[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.94677[/C][C]0.0532299[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]1.29822[/C][C]-0.298223[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]1.14333[/C][C]-0.143326[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.964517[/C][C]0.0354826[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]1.01571[/C][C]-0.0157108[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]1.12897[/C][C]-0.128968[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.871863[/C][C]0.128137[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]1.21926[/C][C]-0.219258[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.954623[/C][C]0.0453774[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.837927[/C][C]0.162073[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]0.97261[/C][C]0.0273903[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.878586[/C][C]0.121414[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.886423[/C][C]0.113577[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.814191[/C][C]0.185809[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]1.40154[/C][C]-0.401536[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.490385[/C][C]-0.490385[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.273964[/C][C]-0.273964[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.151496[/C][C]-0.151496[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.694334[/C][C]-0.694334[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.175972[/C][C]-0.175972[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.194857[/C][C]-0.194857[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.727659[/C][C]-0.727659[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.758372[/C][C]-0.758372[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.780302[/C][C]-0.780302[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.782057[/C][C]-0.782057[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.760087[/C][C]-0.760087[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.673413[/C][C]-0.673413[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.598084[/C][C]0.401916[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.613487[/C][C]0.386513[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.757519[/C][C]0.242481[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.609373[/C][C]0.390627[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.72452[/C][C]0.27548[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.544607[/C][C]0.455393[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.806341[/C][C]-0.806341[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.846662[/C][C]-0.846662[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.750927[/C][C]-0.750927[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.465813[/C][C]-0.465813[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.438237[/C][C]-0.438237[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.64686[/C][C]-0.64686[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.512014[/C][C]-0.512014[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.545608[/C][C]-0.545608[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.575621[/C][C]-0.575621[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.566053[/C][C]-0.566053[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.523304[/C][C]-0.523304[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.706742[/C][C]-0.706742[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111.01648-0.0164817
211.12639-0.126385
311.06775-0.0677493
411.13148-0.131476
511.09977-0.0997721
611.0806-0.0806036
710.839920.16008
810.7349550.265045
910.9718690.0281312
1011.04763-0.047628
1111.08729-0.0872939
1211.09848-0.0984785
1310.5726830.427317
1410.8592750.140725
1510.7510940.248906
1610.8374840.162516
1710.785120.21488
1811.36388-0.363881
1911.19881-0.198813
2010.9765210.0234785
2111.10506-0.105058
2210.9041330.0958668
2311.02894-0.0289409
2410.8376450.162355
2510.8188520.181148
2610.8640220.135978
2710.7265630.273437
2810.6940910.305909
2910.6307630.369237
3010.6541710.345829
3100.326147-0.326147
3200.271545-0.271545
3300.358327-0.358327
3400.263684-0.263684
3500.212797-0.212797
3600.247781-0.247781
3710.5888090.411191
3810.6022970.397703
3910.5236240.476376
4010.6328180.367182
4110.480520.51948
4210.3237780.676222
4300.169958-0.169958
4400.281193-0.281193
4500.184033-0.184033
4600.207119-0.207119
4700.194765-0.194765
4800.302789-0.302789
4900.732376-0.732376
5000.725444-0.725444
5100.684645-0.684645
5200.717185-0.717185
5300.584094-0.584094
5400.663723-0.663723
5510.9643820.035618
5611.02475-0.024749
5711.0227-0.0226969
5811.0278-0.0277962
5911.02618-0.0261812
6010.9127180.0872823
6100.378186-0.378186
6200.364305-0.364305
6300.264077-0.264077
6400.125063-0.125063
6500.116312-0.116312
6600.267563-0.267563
6710.8942880.105712
6810.8889670.111033
6910.7624910.237509
7010.674140.32586
7110.7909090.209091
7210.9182010.0817993
7310.8822640.117736
7410.7203770.279623
7510.8604430.139557
7610.9391630.0608372
7710.9014790.0985206
7810.8928370.107163
7910.977310.02269
8011.01742-0.0174199
8110.9994470.000553014
8210.9429450.0570551
8310.8881450.111855
8410.7013580.298642
8510.9531380.0468624
8610.7565540.243446
8710.6932380.306762
8810.7981490.201851
8910.8449780.155022
9010.9966470.00335342
9111.1075-0.107504
9210.6034040.396596
9310.5772360.422764
9410.7187790.281221
9510.720040.27996
9610.5974710.402529
9710.5882790.411721
9811.07154-0.0715441
9910.8841330.115867
10011.11466-0.114663
10111.11436-0.114361
10211.13878-0.13878
10311.04094-0.0409401
10410.5484380.451562
10510.4771070.522893
10610.54460.4554
10710.5042180.495782
10810.6347690.365231
10910.5408190.459181
11010.7985780.201422
11110.8383860.161614
11210.4346370.565363
11310.704890.29511
11410.5779410.422059
11510.553820.44618
11610.8621120.137888
11710.6883420.311658
11810.9603260.0396738
11910.9267220.0732783
12010.8926050.107395
12110.6512240.348776
12210.9668980.0331019
12310.7924930.207507
12410.7547330.245267
12510.6998530.300147
12610.7417610.258239
12710.7190390.280961
12810.6853320.314668
12910.5830070.416993
13010.7689930.231007
13110.7476640.252336
13210.7568540.243146
13310.9146590.0853407
13410.6698860.330114
13510.994330.00567006
13610.9628870.0371129
13711.07423-0.0742304
13811.05007-0.0500705
13910.9072490.0927512
14010.7981640.201836
14111.03874-0.0387429
14210.8220440.177956
14310.752610.24739
14410.7093940.290606
14510.5605220.439478
14610.8549540.145046
14711.19912-0.199117
14810.9718870.0281134
14911.07459-0.0745914
15010.6020750.397925
15110.946770.0532299
15211.29822-0.298223
15311.14333-0.143326
15410.9645170.0354826
15511.01571-0.0157108
15611.12897-0.128968
15710.8718630.128137
15811.21926-0.219258
15910.9546230.0453774
16010.8379270.162073
16110.972610.0273903
16210.8785860.121414
16310.8864230.113577
16410.8141910.185809
16511.40154-0.401536
16600.490385-0.490385
16700.273964-0.273964
16800.151496-0.151496
16900.694334-0.694334
17000.175972-0.175972
17100.194857-0.194857
17200.727659-0.727659
17300.758372-0.758372
17400.780302-0.780302
17500.782057-0.782057
17600.760087-0.760087
17700.673413-0.673413
17810.5980840.401916
17910.6134870.386513
18010.7575190.242481
18110.6093730.390627
18210.724520.27548
18310.5446070.455393
18400.806341-0.806341
18500.846662-0.846662
18600.750927-0.750927
18700.465813-0.465813
18800.438237-0.438237
18900.64686-0.64686
19000.512014-0.512014
19100.545608-0.545608
19200.575621-0.575621
19300.566053-0.566053
19400.523304-0.523304
19500.706742-0.706742







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
93.42561e-516.85121e-511
105.05735e-681.01147e-671
115.15362e-831.03072e-821
121.75905e-963.51809e-961
133.4637e-1306.92741e-1301
148.87868e-1231.77574e-1221
155.1483e-1371.02966e-1361
16001
173.92241e-1817.84482e-1811
185.34956e-1811.06991e-1801
191.0477e-1962.09539e-1961
201.03097e-2242.06193e-2241
218.70749e-2601.7415e-2591
224.38934e-2408.77869e-2401
231.71284e-2593.42567e-2591
241.73024e-2703.46047e-2701
252.97134e-2975.94268e-2971
26001
27001
28001
29001
30001
318.06959e-091.61392e-081
321.69231e-083.38462e-081
331.66285e-083.32569e-081
346.77887e-091.35577e-081
352.49536e-094.99071e-091
369.3968e-101.87936e-091
377.24455e-071.44891e-060.999999
388.68912e-061.73782e-050.999991
390.0001123980.0002247960.999888
400.0005016910.001003380.999498
410.001658080.003316160.998342
420.0026530.005305990.997347
430.002370810.004741620.997629
440.001834190.003668390.998166
450.001382960.002765920.998617
460.001022660.002045310.998977
470.0006825680.001365140.999317
480.0005056860.001011370.999494
490.006847280.01369460.993153
500.02967310.05934620.970327
510.06957420.1391480.930426
520.116390.2327790.88361
530.1644360.3288710.835564
540.2220670.4441340.777933
550.1951670.3903340.804833
560.1700810.3401620.829919
570.1438330.2876660.856167
580.1194750.2389490.880525
590.09754180.1950840.902458
600.08895490.177910.911045
610.1480060.2960110.851994
620.1714570.3429150.828543
630.1635350.327070.836465
640.1449680.2899350.855032
650.126140.2522790.87386
660.1272340.2544680.872766
670.1079830.2159670.892017
680.09007590.1801520.909924
690.07988690.1597740.920113
700.07600660.1520130.923993
710.06538090.1307620.934619
720.05308170.1061630.946918
730.04826570.09653140.951734
740.04374230.08748460.956258
750.03525330.07050650.964747
760.02900430.05800860.970996
770.02482650.0496530.975174
780.01960170.03920330.980398
790.01495470.02990930.985045
800.01134160.02268320.988658
810.009315790.01863160.990684
820.006974810.01394960.993025
830.005323970.01064790.994676
840.004605020.009210040.995395
850.003528040.007056090.996472
860.003734880.007469750.996265
870.004546850.009093710.995453
880.003800030.007600060.9962
890.002963710.005927410.997036
900.002150510.004301020.997849
910.001577050.00315410.998423
920.001945720.003891440.998054
930.002227430.004454860.997773
940.001991340.003982670.998009
950.00177270.003545410.998227
960.002094060.004188120.997906
970.002514660.005029320.997485
980.00186340.00372680.998137
990.00139040.002780810.99861
1000.001073720.002147450.998926
1010.0007948330.001589670.999205
1020.0005882970.001176590.999412
1030.000622430.001244860.999378
1040.0007792690.001558540.999221
1050.001164280.002328550.998836
1060.00144650.0028930.998554
1070.001985420.003970840.998015
1080.002048960.004097920.997951
1090.002565150.005130290.997435
1100.002107140.004214270.997893
1110.001673080.003346160.998327
1120.003195750.00639150.996804
1130.0031710.0063420.996829
1140.00396070.00792140.996039
1150.005066570.01013310.994933
1160.004031350.00806270.995969
1170.003750880.007501760.996249
1180.002771280.005542570.997229
1190.002040860.004081720.997959
1200.001541050.00308210.998459
1210.001695350.00339070.998305
1220.001245550.00249110.998754
1230.001099410.002198810.998901
1240.001100030.002200060.9989
1250.001247230.002494460.998753
1260.00141810.002836190.998582
1270.002087220.004174440.997913
1280.003881670.007763340.996118
1290.005117490.0102350.994883
1300.004920820.009841640.995079
1310.004866410.009732810.995134
1320.004625410.009250820.995375
1330.003739530.007479060.99626
1340.00466860.00933720.995331
1350.003374480.006748950.996626
1360.002411760.004823520.997588
1370.001712770.003425550.998287
1380.001202230.002404460.998798
1390.0008632120.001726420.999137
1400.000801120.001602240.999199
1410.0005414610.001082920.999459
1420.000528650.00105730.999471
1430.000478340.000956680.999522
1440.0009568480.00191370.999043
1450.001688470.003376950.998312
1460.002271850.00454370.997728
1470.00175030.00350060.99825
1480.001216140.002432280.998784
1490.000829140.001658280.999171
1500.001186530.002373060.998813
1510.00087160.00174320.999128
1520.0008357350.001671470.999164
1530.0007105790.001421160.999289
1540.0005372260.001074450.999463
1550.0004534450.0009068910.999547
1560.000326610.0006532210.999673
1570.0003424140.0006848280.999658
1580.0002301750.000460350.99977
1590.0001765010.0003530020.999823
1600.0001831450.0003662890.999817
1610.0001947030.0003894050.999805
1620.0002172890.0004345790.999783
1630.0003315610.0006631220.999668
1640.0008326370.001665270.999167
1650.0005922790.001184560.999408
1660.0005997370.001199470.9994
1670.0007103470.001420690.99929
1680.0009163870.001832770.999084
1690.001191780.002383560.998808
1700.001698350.003396710.998302
1710.9995160.0009671040.000483552
1720.9998050.0003893930.000194697
1730.9997040.000592190.000296095
1740.9995180.0009645630.000482281
1750.9994890.001021160.00051058
1760.9999030.0001932789.66389e-05
1770.9998680.0002645740.000132287
1780.9997540.0004919810.00024599
1790.9993180.001364220.000682109
1800.9988380.00232350.00116175
1810.9969560.006087240.00304362
1820.9929710.01405780.00702889
183100
184100
185100
186100

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 3.42561e-51 & 6.85121e-51 & 1 \tabularnewline
10 & 5.05735e-68 & 1.01147e-67 & 1 \tabularnewline
11 & 5.15362e-83 & 1.03072e-82 & 1 \tabularnewline
12 & 1.75905e-96 & 3.51809e-96 & 1 \tabularnewline
13 & 3.4637e-130 & 6.92741e-130 & 1 \tabularnewline
14 & 8.87868e-123 & 1.77574e-122 & 1 \tabularnewline
15 & 5.1483e-137 & 1.02966e-136 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 3.92241e-181 & 7.84482e-181 & 1 \tabularnewline
18 & 5.34956e-181 & 1.06991e-180 & 1 \tabularnewline
19 & 1.0477e-196 & 2.09539e-196 & 1 \tabularnewline
20 & 1.03097e-224 & 2.06193e-224 & 1 \tabularnewline
21 & 8.70749e-260 & 1.7415e-259 & 1 \tabularnewline
22 & 4.38934e-240 & 8.77869e-240 & 1 \tabularnewline
23 & 1.71284e-259 & 3.42567e-259 & 1 \tabularnewline
24 & 1.73024e-270 & 3.46047e-270 & 1 \tabularnewline
25 & 2.97134e-297 & 5.94268e-297 & 1 \tabularnewline
26 & 0 & 0 & 1 \tabularnewline
27 & 0 & 0 & 1 \tabularnewline
28 & 0 & 0 & 1 \tabularnewline
29 & 0 & 0 & 1 \tabularnewline
30 & 0 & 0 & 1 \tabularnewline
31 & 8.06959e-09 & 1.61392e-08 & 1 \tabularnewline
32 & 1.69231e-08 & 3.38462e-08 & 1 \tabularnewline
33 & 1.66285e-08 & 3.32569e-08 & 1 \tabularnewline
34 & 6.77887e-09 & 1.35577e-08 & 1 \tabularnewline
35 & 2.49536e-09 & 4.99071e-09 & 1 \tabularnewline
36 & 9.3968e-10 & 1.87936e-09 & 1 \tabularnewline
37 & 7.24455e-07 & 1.44891e-06 & 0.999999 \tabularnewline
38 & 8.68912e-06 & 1.73782e-05 & 0.999991 \tabularnewline
39 & 0.000112398 & 0.000224796 & 0.999888 \tabularnewline
40 & 0.000501691 & 0.00100338 & 0.999498 \tabularnewline
41 & 0.00165808 & 0.00331616 & 0.998342 \tabularnewline
42 & 0.002653 & 0.00530599 & 0.997347 \tabularnewline
43 & 0.00237081 & 0.00474162 & 0.997629 \tabularnewline
44 & 0.00183419 & 0.00366839 & 0.998166 \tabularnewline
45 & 0.00138296 & 0.00276592 & 0.998617 \tabularnewline
46 & 0.00102266 & 0.00204531 & 0.998977 \tabularnewline
47 & 0.000682568 & 0.00136514 & 0.999317 \tabularnewline
48 & 0.000505686 & 0.00101137 & 0.999494 \tabularnewline
49 & 0.00684728 & 0.0136946 & 0.993153 \tabularnewline
50 & 0.0296731 & 0.0593462 & 0.970327 \tabularnewline
51 & 0.0695742 & 0.139148 & 0.930426 \tabularnewline
52 & 0.11639 & 0.232779 & 0.88361 \tabularnewline
53 & 0.164436 & 0.328871 & 0.835564 \tabularnewline
54 & 0.222067 & 0.444134 & 0.777933 \tabularnewline
55 & 0.195167 & 0.390334 & 0.804833 \tabularnewline
56 & 0.170081 & 0.340162 & 0.829919 \tabularnewline
57 & 0.143833 & 0.287666 & 0.856167 \tabularnewline
58 & 0.119475 & 0.238949 & 0.880525 \tabularnewline
59 & 0.0975418 & 0.195084 & 0.902458 \tabularnewline
60 & 0.0889549 & 0.17791 & 0.911045 \tabularnewline
61 & 0.148006 & 0.296011 & 0.851994 \tabularnewline
62 & 0.171457 & 0.342915 & 0.828543 \tabularnewline
63 & 0.163535 & 0.32707 & 0.836465 \tabularnewline
64 & 0.144968 & 0.289935 & 0.855032 \tabularnewline
65 & 0.12614 & 0.252279 & 0.87386 \tabularnewline
66 & 0.127234 & 0.254468 & 0.872766 \tabularnewline
67 & 0.107983 & 0.215967 & 0.892017 \tabularnewline
68 & 0.0900759 & 0.180152 & 0.909924 \tabularnewline
69 & 0.0798869 & 0.159774 & 0.920113 \tabularnewline
70 & 0.0760066 & 0.152013 & 0.923993 \tabularnewline
71 & 0.0653809 & 0.130762 & 0.934619 \tabularnewline
72 & 0.0530817 & 0.106163 & 0.946918 \tabularnewline
73 & 0.0482657 & 0.0965314 & 0.951734 \tabularnewline
74 & 0.0437423 & 0.0874846 & 0.956258 \tabularnewline
75 & 0.0352533 & 0.0705065 & 0.964747 \tabularnewline
76 & 0.0290043 & 0.0580086 & 0.970996 \tabularnewline
77 & 0.0248265 & 0.049653 & 0.975174 \tabularnewline
78 & 0.0196017 & 0.0392033 & 0.980398 \tabularnewline
79 & 0.0149547 & 0.0299093 & 0.985045 \tabularnewline
80 & 0.0113416 & 0.0226832 & 0.988658 \tabularnewline
81 & 0.00931579 & 0.0186316 & 0.990684 \tabularnewline
82 & 0.00697481 & 0.0139496 & 0.993025 \tabularnewline
83 & 0.00532397 & 0.0106479 & 0.994676 \tabularnewline
84 & 0.00460502 & 0.00921004 & 0.995395 \tabularnewline
85 & 0.00352804 & 0.00705609 & 0.996472 \tabularnewline
86 & 0.00373488 & 0.00746975 & 0.996265 \tabularnewline
87 & 0.00454685 & 0.00909371 & 0.995453 \tabularnewline
88 & 0.00380003 & 0.00760006 & 0.9962 \tabularnewline
89 & 0.00296371 & 0.00592741 & 0.997036 \tabularnewline
90 & 0.00215051 & 0.00430102 & 0.997849 \tabularnewline
91 & 0.00157705 & 0.0031541 & 0.998423 \tabularnewline
92 & 0.00194572 & 0.00389144 & 0.998054 \tabularnewline
93 & 0.00222743 & 0.00445486 & 0.997773 \tabularnewline
94 & 0.00199134 & 0.00398267 & 0.998009 \tabularnewline
95 & 0.0017727 & 0.00354541 & 0.998227 \tabularnewline
96 & 0.00209406 & 0.00418812 & 0.997906 \tabularnewline
97 & 0.00251466 & 0.00502932 & 0.997485 \tabularnewline
98 & 0.0018634 & 0.0037268 & 0.998137 \tabularnewline
99 & 0.0013904 & 0.00278081 & 0.99861 \tabularnewline
100 & 0.00107372 & 0.00214745 & 0.998926 \tabularnewline
101 & 0.000794833 & 0.00158967 & 0.999205 \tabularnewline
102 & 0.000588297 & 0.00117659 & 0.999412 \tabularnewline
103 & 0.00062243 & 0.00124486 & 0.999378 \tabularnewline
104 & 0.000779269 & 0.00155854 & 0.999221 \tabularnewline
105 & 0.00116428 & 0.00232855 & 0.998836 \tabularnewline
106 & 0.0014465 & 0.002893 & 0.998554 \tabularnewline
107 & 0.00198542 & 0.00397084 & 0.998015 \tabularnewline
108 & 0.00204896 & 0.00409792 & 0.997951 \tabularnewline
109 & 0.00256515 & 0.00513029 & 0.997435 \tabularnewline
110 & 0.00210714 & 0.00421427 & 0.997893 \tabularnewline
111 & 0.00167308 & 0.00334616 & 0.998327 \tabularnewline
112 & 0.00319575 & 0.0063915 & 0.996804 \tabularnewline
113 & 0.003171 & 0.006342 & 0.996829 \tabularnewline
114 & 0.0039607 & 0.0079214 & 0.996039 \tabularnewline
115 & 0.00506657 & 0.0101331 & 0.994933 \tabularnewline
116 & 0.00403135 & 0.0080627 & 0.995969 \tabularnewline
117 & 0.00375088 & 0.00750176 & 0.996249 \tabularnewline
118 & 0.00277128 & 0.00554257 & 0.997229 \tabularnewline
119 & 0.00204086 & 0.00408172 & 0.997959 \tabularnewline
120 & 0.00154105 & 0.0030821 & 0.998459 \tabularnewline
121 & 0.00169535 & 0.0033907 & 0.998305 \tabularnewline
122 & 0.00124555 & 0.0024911 & 0.998754 \tabularnewline
123 & 0.00109941 & 0.00219881 & 0.998901 \tabularnewline
124 & 0.00110003 & 0.00220006 & 0.9989 \tabularnewline
125 & 0.00124723 & 0.00249446 & 0.998753 \tabularnewline
126 & 0.0014181 & 0.00283619 & 0.998582 \tabularnewline
127 & 0.00208722 & 0.00417444 & 0.997913 \tabularnewline
128 & 0.00388167 & 0.00776334 & 0.996118 \tabularnewline
129 & 0.00511749 & 0.010235 & 0.994883 \tabularnewline
130 & 0.00492082 & 0.00984164 & 0.995079 \tabularnewline
131 & 0.00486641 & 0.00973281 & 0.995134 \tabularnewline
132 & 0.00462541 & 0.00925082 & 0.995375 \tabularnewline
133 & 0.00373953 & 0.00747906 & 0.99626 \tabularnewline
134 & 0.0046686 & 0.0093372 & 0.995331 \tabularnewline
135 & 0.00337448 & 0.00674895 & 0.996626 \tabularnewline
136 & 0.00241176 & 0.00482352 & 0.997588 \tabularnewline
137 & 0.00171277 & 0.00342555 & 0.998287 \tabularnewline
138 & 0.00120223 & 0.00240446 & 0.998798 \tabularnewline
139 & 0.000863212 & 0.00172642 & 0.999137 \tabularnewline
140 & 0.00080112 & 0.00160224 & 0.999199 \tabularnewline
141 & 0.000541461 & 0.00108292 & 0.999459 \tabularnewline
142 & 0.00052865 & 0.0010573 & 0.999471 \tabularnewline
143 & 0.00047834 & 0.00095668 & 0.999522 \tabularnewline
144 & 0.000956848 & 0.0019137 & 0.999043 \tabularnewline
145 & 0.00168847 & 0.00337695 & 0.998312 \tabularnewline
146 & 0.00227185 & 0.0045437 & 0.997728 \tabularnewline
147 & 0.0017503 & 0.0035006 & 0.99825 \tabularnewline
148 & 0.00121614 & 0.00243228 & 0.998784 \tabularnewline
149 & 0.00082914 & 0.00165828 & 0.999171 \tabularnewline
150 & 0.00118653 & 0.00237306 & 0.998813 \tabularnewline
151 & 0.0008716 & 0.0017432 & 0.999128 \tabularnewline
152 & 0.000835735 & 0.00167147 & 0.999164 \tabularnewline
153 & 0.000710579 & 0.00142116 & 0.999289 \tabularnewline
154 & 0.000537226 & 0.00107445 & 0.999463 \tabularnewline
155 & 0.000453445 & 0.000906891 & 0.999547 \tabularnewline
156 & 0.00032661 & 0.000653221 & 0.999673 \tabularnewline
157 & 0.000342414 & 0.000684828 & 0.999658 \tabularnewline
158 & 0.000230175 & 0.00046035 & 0.99977 \tabularnewline
159 & 0.000176501 & 0.000353002 & 0.999823 \tabularnewline
160 & 0.000183145 & 0.000366289 & 0.999817 \tabularnewline
161 & 0.000194703 & 0.000389405 & 0.999805 \tabularnewline
162 & 0.000217289 & 0.000434579 & 0.999783 \tabularnewline
163 & 0.000331561 & 0.000663122 & 0.999668 \tabularnewline
164 & 0.000832637 & 0.00166527 & 0.999167 \tabularnewline
165 & 0.000592279 & 0.00118456 & 0.999408 \tabularnewline
166 & 0.000599737 & 0.00119947 & 0.9994 \tabularnewline
167 & 0.000710347 & 0.00142069 & 0.99929 \tabularnewline
168 & 0.000916387 & 0.00183277 & 0.999084 \tabularnewline
169 & 0.00119178 & 0.00238356 & 0.998808 \tabularnewline
170 & 0.00169835 & 0.00339671 & 0.998302 \tabularnewline
171 & 0.999516 & 0.000967104 & 0.000483552 \tabularnewline
172 & 0.999805 & 0.000389393 & 0.000194697 \tabularnewline
173 & 0.999704 & 0.00059219 & 0.000296095 \tabularnewline
174 & 0.999518 & 0.000964563 & 0.000482281 \tabularnewline
175 & 0.999489 & 0.00102116 & 0.00051058 \tabularnewline
176 & 0.999903 & 0.000193278 & 9.66389e-05 \tabularnewline
177 & 0.999868 & 0.000264574 & 0.000132287 \tabularnewline
178 & 0.999754 & 0.000491981 & 0.00024599 \tabularnewline
179 & 0.999318 & 0.00136422 & 0.000682109 \tabularnewline
180 & 0.998838 & 0.0023235 & 0.00116175 \tabularnewline
181 & 0.996956 & 0.00608724 & 0.00304362 \tabularnewline
182 & 0.992971 & 0.0140578 & 0.00702889 \tabularnewline
183 & 1 & 0 & 0 \tabularnewline
184 & 1 & 0 & 0 \tabularnewline
185 & 1 & 0 & 0 \tabularnewline
186 & 1 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]3.42561e-51[/C][C]6.85121e-51[/C][C]1[/C][/ROW]
[ROW][C]10[/C][C]5.05735e-68[/C][C]1.01147e-67[/C][C]1[/C][/ROW]
[ROW][C]11[/C][C]5.15362e-83[/C][C]1.03072e-82[/C][C]1[/C][/ROW]
[ROW][C]12[/C][C]1.75905e-96[/C][C]3.51809e-96[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]3.4637e-130[/C][C]6.92741e-130[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]8.87868e-123[/C][C]1.77574e-122[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]5.1483e-137[/C][C]1.02966e-136[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]3.92241e-181[/C][C]7.84482e-181[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]5.34956e-181[/C][C]1.06991e-180[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]1.0477e-196[/C][C]2.09539e-196[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]1.03097e-224[/C][C]2.06193e-224[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]8.70749e-260[/C][C]1.7415e-259[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]4.38934e-240[/C][C]8.77869e-240[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.71284e-259[/C][C]3.42567e-259[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]1.73024e-270[/C][C]3.46047e-270[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]2.97134e-297[/C][C]5.94268e-297[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]8.06959e-09[/C][C]1.61392e-08[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]1.69231e-08[/C][C]3.38462e-08[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]1.66285e-08[/C][C]3.32569e-08[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]6.77887e-09[/C][C]1.35577e-08[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]2.49536e-09[/C][C]4.99071e-09[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]9.3968e-10[/C][C]1.87936e-09[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]7.24455e-07[/C][C]1.44891e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]38[/C][C]8.68912e-06[/C][C]1.73782e-05[/C][C]0.999991[/C][/ROW]
[ROW][C]39[/C][C]0.000112398[/C][C]0.000224796[/C][C]0.999888[/C][/ROW]
[ROW][C]40[/C][C]0.000501691[/C][C]0.00100338[/C][C]0.999498[/C][/ROW]
[ROW][C]41[/C][C]0.00165808[/C][C]0.00331616[/C][C]0.998342[/C][/ROW]
[ROW][C]42[/C][C]0.002653[/C][C]0.00530599[/C][C]0.997347[/C][/ROW]
[ROW][C]43[/C][C]0.00237081[/C][C]0.00474162[/C][C]0.997629[/C][/ROW]
[ROW][C]44[/C][C]0.00183419[/C][C]0.00366839[/C][C]0.998166[/C][/ROW]
[ROW][C]45[/C][C]0.00138296[/C][C]0.00276592[/C][C]0.998617[/C][/ROW]
[ROW][C]46[/C][C]0.00102266[/C][C]0.00204531[/C][C]0.998977[/C][/ROW]
[ROW][C]47[/C][C]0.000682568[/C][C]0.00136514[/C][C]0.999317[/C][/ROW]
[ROW][C]48[/C][C]0.000505686[/C][C]0.00101137[/C][C]0.999494[/C][/ROW]
[ROW][C]49[/C][C]0.00684728[/C][C]0.0136946[/C][C]0.993153[/C][/ROW]
[ROW][C]50[/C][C]0.0296731[/C][C]0.0593462[/C][C]0.970327[/C][/ROW]
[ROW][C]51[/C][C]0.0695742[/C][C]0.139148[/C][C]0.930426[/C][/ROW]
[ROW][C]52[/C][C]0.11639[/C][C]0.232779[/C][C]0.88361[/C][/ROW]
[ROW][C]53[/C][C]0.164436[/C][C]0.328871[/C][C]0.835564[/C][/ROW]
[ROW][C]54[/C][C]0.222067[/C][C]0.444134[/C][C]0.777933[/C][/ROW]
[ROW][C]55[/C][C]0.195167[/C][C]0.390334[/C][C]0.804833[/C][/ROW]
[ROW][C]56[/C][C]0.170081[/C][C]0.340162[/C][C]0.829919[/C][/ROW]
[ROW][C]57[/C][C]0.143833[/C][C]0.287666[/C][C]0.856167[/C][/ROW]
[ROW][C]58[/C][C]0.119475[/C][C]0.238949[/C][C]0.880525[/C][/ROW]
[ROW][C]59[/C][C]0.0975418[/C][C]0.195084[/C][C]0.902458[/C][/ROW]
[ROW][C]60[/C][C]0.0889549[/C][C]0.17791[/C][C]0.911045[/C][/ROW]
[ROW][C]61[/C][C]0.148006[/C][C]0.296011[/C][C]0.851994[/C][/ROW]
[ROW][C]62[/C][C]0.171457[/C][C]0.342915[/C][C]0.828543[/C][/ROW]
[ROW][C]63[/C][C]0.163535[/C][C]0.32707[/C][C]0.836465[/C][/ROW]
[ROW][C]64[/C][C]0.144968[/C][C]0.289935[/C][C]0.855032[/C][/ROW]
[ROW][C]65[/C][C]0.12614[/C][C]0.252279[/C][C]0.87386[/C][/ROW]
[ROW][C]66[/C][C]0.127234[/C][C]0.254468[/C][C]0.872766[/C][/ROW]
[ROW][C]67[/C][C]0.107983[/C][C]0.215967[/C][C]0.892017[/C][/ROW]
[ROW][C]68[/C][C]0.0900759[/C][C]0.180152[/C][C]0.909924[/C][/ROW]
[ROW][C]69[/C][C]0.0798869[/C][C]0.159774[/C][C]0.920113[/C][/ROW]
[ROW][C]70[/C][C]0.0760066[/C][C]0.152013[/C][C]0.923993[/C][/ROW]
[ROW][C]71[/C][C]0.0653809[/C][C]0.130762[/C][C]0.934619[/C][/ROW]
[ROW][C]72[/C][C]0.0530817[/C][C]0.106163[/C][C]0.946918[/C][/ROW]
[ROW][C]73[/C][C]0.0482657[/C][C]0.0965314[/C][C]0.951734[/C][/ROW]
[ROW][C]74[/C][C]0.0437423[/C][C]0.0874846[/C][C]0.956258[/C][/ROW]
[ROW][C]75[/C][C]0.0352533[/C][C]0.0705065[/C][C]0.964747[/C][/ROW]
[ROW][C]76[/C][C]0.0290043[/C][C]0.0580086[/C][C]0.970996[/C][/ROW]
[ROW][C]77[/C][C]0.0248265[/C][C]0.049653[/C][C]0.975174[/C][/ROW]
[ROW][C]78[/C][C]0.0196017[/C][C]0.0392033[/C][C]0.980398[/C][/ROW]
[ROW][C]79[/C][C]0.0149547[/C][C]0.0299093[/C][C]0.985045[/C][/ROW]
[ROW][C]80[/C][C]0.0113416[/C][C]0.0226832[/C][C]0.988658[/C][/ROW]
[ROW][C]81[/C][C]0.00931579[/C][C]0.0186316[/C][C]0.990684[/C][/ROW]
[ROW][C]82[/C][C]0.00697481[/C][C]0.0139496[/C][C]0.993025[/C][/ROW]
[ROW][C]83[/C][C]0.00532397[/C][C]0.0106479[/C][C]0.994676[/C][/ROW]
[ROW][C]84[/C][C]0.00460502[/C][C]0.00921004[/C][C]0.995395[/C][/ROW]
[ROW][C]85[/C][C]0.00352804[/C][C]0.00705609[/C][C]0.996472[/C][/ROW]
[ROW][C]86[/C][C]0.00373488[/C][C]0.00746975[/C][C]0.996265[/C][/ROW]
[ROW][C]87[/C][C]0.00454685[/C][C]0.00909371[/C][C]0.995453[/C][/ROW]
[ROW][C]88[/C][C]0.00380003[/C][C]0.00760006[/C][C]0.9962[/C][/ROW]
[ROW][C]89[/C][C]0.00296371[/C][C]0.00592741[/C][C]0.997036[/C][/ROW]
[ROW][C]90[/C][C]0.00215051[/C][C]0.00430102[/C][C]0.997849[/C][/ROW]
[ROW][C]91[/C][C]0.00157705[/C][C]0.0031541[/C][C]0.998423[/C][/ROW]
[ROW][C]92[/C][C]0.00194572[/C][C]0.00389144[/C][C]0.998054[/C][/ROW]
[ROW][C]93[/C][C]0.00222743[/C][C]0.00445486[/C][C]0.997773[/C][/ROW]
[ROW][C]94[/C][C]0.00199134[/C][C]0.00398267[/C][C]0.998009[/C][/ROW]
[ROW][C]95[/C][C]0.0017727[/C][C]0.00354541[/C][C]0.998227[/C][/ROW]
[ROW][C]96[/C][C]0.00209406[/C][C]0.00418812[/C][C]0.997906[/C][/ROW]
[ROW][C]97[/C][C]0.00251466[/C][C]0.00502932[/C][C]0.997485[/C][/ROW]
[ROW][C]98[/C][C]0.0018634[/C][C]0.0037268[/C][C]0.998137[/C][/ROW]
[ROW][C]99[/C][C]0.0013904[/C][C]0.00278081[/C][C]0.99861[/C][/ROW]
[ROW][C]100[/C][C]0.00107372[/C][C]0.00214745[/C][C]0.998926[/C][/ROW]
[ROW][C]101[/C][C]0.000794833[/C][C]0.00158967[/C][C]0.999205[/C][/ROW]
[ROW][C]102[/C][C]0.000588297[/C][C]0.00117659[/C][C]0.999412[/C][/ROW]
[ROW][C]103[/C][C]0.00062243[/C][C]0.00124486[/C][C]0.999378[/C][/ROW]
[ROW][C]104[/C][C]0.000779269[/C][C]0.00155854[/C][C]0.999221[/C][/ROW]
[ROW][C]105[/C][C]0.00116428[/C][C]0.00232855[/C][C]0.998836[/C][/ROW]
[ROW][C]106[/C][C]0.0014465[/C][C]0.002893[/C][C]0.998554[/C][/ROW]
[ROW][C]107[/C][C]0.00198542[/C][C]0.00397084[/C][C]0.998015[/C][/ROW]
[ROW][C]108[/C][C]0.00204896[/C][C]0.00409792[/C][C]0.997951[/C][/ROW]
[ROW][C]109[/C][C]0.00256515[/C][C]0.00513029[/C][C]0.997435[/C][/ROW]
[ROW][C]110[/C][C]0.00210714[/C][C]0.00421427[/C][C]0.997893[/C][/ROW]
[ROW][C]111[/C][C]0.00167308[/C][C]0.00334616[/C][C]0.998327[/C][/ROW]
[ROW][C]112[/C][C]0.00319575[/C][C]0.0063915[/C][C]0.996804[/C][/ROW]
[ROW][C]113[/C][C]0.003171[/C][C]0.006342[/C][C]0.996829[/C][/ROW]
[ROW][C]114[/C][C]0.0039607[/C][C]0.0079214[/C][C]0.996039[/C][/ROW]
[ROW][C]115[/C][C]0.00506657[/C][C]0.0101331[/C][C]0.994933[/C][/ROW]
[ROW][C]116[/C][C]0.00403135[/C][C]0.0080627[/C][C]0.995969[/C][/ROW]
[ROW][C]117[/C][C]0.00375088[/C][C]0.00750176[/C][C]0.996249[/C][/ROW]
[ROW][C]118[/C][C]0.00277128[/C][C]0.00554257[/C][C]0.997229[/C][/ROW]
[ROW][C]119[/C][C]0.00204086[/C][C]0.00408172[/C][C]0.997959[/C][/ROW]
[ROW][C]120[/C][C]0.00154105[/C][C]0.0030821[/C][C]0.998459[/C][/ROW]
[ROW][C]121[/C][C]0.00169535[/C][C]0.0033907[/C][C]0.998305[/C][/ROW]
[ROW][C]122[/C][C]0.00124555[/C][C]0.0024911[/C][C]0.998754[/C][/ROW]
[ROW][C]123[/C][C]0.00109941[/C][C]0.00219881[/C][C]0.998901[/C][/ROW]
[ROW][C]124[/C][C]0.00110003[/C][C]0.00220006[/C][C]0.9989[/C][/ROW]
[ROW][C]125[/C][C]0.00124723[/C][C]0.00249446[/C][C]0.998753[/C][/ROW]
[ROW][C]126[/C][C]0.0014181[/C][C]0.00283619[/C][C]0.998582[/C][/ROW]
[ROW][C]127[/C][C]0.00208722[/C][C]0.00417444[/C][C]0.997913[/C][/ROW]
[ROW][C]128[/C][C]0.00388167[/C][C]0.00776334[/C][C]0.996118[/C][/ROW]
[ROW][C]129[/C][C]0.00511749[/C][C]0.010235[/C][C]0.994883[/C][/ROW]
[ROW][C]130[/C][C]0.00492082[/C][C]0.00984164[/C][C]0.995079[/C][/ROW]
[ROW][C]131[/C][C]0.00486641[/C][C]0.00973281[/C][C]0.995134[/C][/ROW]
[ROW][C]132[/C][C]0.00462541[/C][C]0.00925082[/C][C]0.995375[/C][/ROW]
[ROW][C]133[/C][C]0.00373953[/C][C]0.00747906[/C][C]0.99626[/C][/ROW]
[ROW][C]134[/C][C]0.0046686[/C][C]0.0093372[/C][C]0.995331[/C][/ROW]
[ROW][C]135[/C][C]0.00337448[/C][C]0.00674895[/C][C]0.996626[/C][/ROW]
[ROW][C]136[/C][C]0.00241176[/C][C]0.00482352[/C][C]0.997588[/C][/ROW]
[ROW][C]137[/C][C]0.00171277[/C][C]0.00342555[/C][C]0.998287[/C][/ROW]
[ROW][C]138[/C][C]0.00120223[/C][C]0.00240446[/C][C]0.998798[/C][/ROW]
[ROW][C]139[/C][C]0.000863212[/C][C]0.00172642[/C][C]0.999137[/C][/ROW]
[ROW][C]140[/C][C]0.00080112[/C][C]0.00160224[/C][C]0.999199[/C][/ROW]
[ROW][C]141[/C][C]0.000541461[/C][C]0.00108292[/C][C]0.999459[/C][/ROW]
[ROW][C]142[/C][C]0.00052865[/C][C]0.0010573[/C][C]0.999471[/C][/ROW]
[ROW][C]143[/C][C]0.00047834[/C][C]0.00095668[/C][C]0.999522[/C][/ROW]
[ROW][C]144[/C][C]0.000956848[/C][C]0.0019137[/C][C]0.999043[/C][/ROW]
[ROW][C]145[/C][C]0.00168847[/C][C]0.00337695[/C][C]0.998312[/C][/ROW]
[ROW][C]146[/C][C]0.00227185[/C][C]0.0045437[/C][C]0.997728[/C][/ROW]
[ROW][C]147[/C][C]0.0017503[/C][C]0.0035006[/C][C]0.99825[/C][/ROW]
[ROW][C]148[/C][C]0.00121614[/C][C]0.00243228[/C][C]0.998784[/C][/ROW]
[ROW][C]149[/C][C]0.00082914[/C][C]0.00165828[/C][C]0.999171[/C][/ROW]
[ROW][C]150[/C][C]0.00118653[/C][C]0.00237306[/C][C]0.998813[/C][/ROW]
[ROW][C]151[/C][C]0.0008716[/C][C]0.0017432[/C][C]0.999128[/C][/ROW]
[ROW][C]152[/C][C]0.000835735[/C][C]0.00167147[/C][C]0.999164[/C][/ROW]
[ROW][C]153[/C][C]0.000710579[/C][C]0.00142116[/C][C]0.999289[/C][/ROW]
[ROW][C]154[/C][C]0.000537226[/C][C]0.00107445[/C][C]0.999463[/C][/ROW]
[ROW][C]155[/C][C]0.000453445[/C][C]0.000906891[/C][C]0.999547[/C][/ROW]
[ROW][C]156[/C][C]0.00032661[/C][C]0.000653221[/C][C]0.999673[/C][/ROW]
[ROW][C]157[/C][C]0.000342414[/C][C]0.000684828[/C][C]0.999658[/C][/ROW]
[ROW][C]158[/C][C]0.000230175[/C][C]0.00046035[/C][C]0.99977[/C][/ROW]
[ROW][C]159[/C][C]0.000176501[/C][C]0.000353002[/C][C]0.999823[/C][/ROW]
[ROW][C]160[/C][C]0.000183145[/C][C]0.000366289[/C][C]0.999817[/C][/ROW]
[ROW][C]161[/C][C]0.000194703[/C][C]0.000389405[/C][C]0.999805[/C][/ROW]
[ROW][C]162[/C][C]0.000217289[/C][C]0.000434579[/C][C]0.999783[/C][/ROW]
[ROW][C]163[/C][C]0.000331561[/C][C]0.000663122[/C][C]0.999668[/C][/ROW]
[ROW][C]164[/C][C]0.000832637[/C][C]0.00166527[/C][C]0.999167[/C][/ROW]
[ROW][C]165[/C][C]0.000592279[/C][C]0.00118456[/C][C]0.999408[/C][/ROW]
[ROW][C]166[/C][C]0.000599737[/C][C]0.00119947[/C][C]0.9994[/C][/ROW]
[ROW][C]167[/C][C]0.000710347[/C][C]0.00142069[/C][C]0.99929[/C][/ROW]
[ROW][C]168[/C][C]0.000916387[/C][C]0.00183277[/C][C]0.999084[/C][/ROW]
[ROW][C]169[/C][C]0.00119178[/C][C]0.00238356[/C][C]0.998808[/C][/ROW]
[ROW][C]170[/C][C]0.00169835[/C][C]0.00339671[/C][C]0.998302[/C][/ROW]
[ROW][C]171[/C][C]0.999516[/C][C]0.000967104[/C][C]0.000483552[/C][/ROW]
[ROW][C]172[/C][C]0.999805[/C][C]0.000389393[/C][C]0.000194697[/C][/ROW]
[ROW][C]173[/C][C]0.999704[/C][C]0.00059219[/C][C]0.000296095[/C][/ROW]
[ROW][C]174[/C][C]0.999518[/C][C]0.000964563[/C][C]0.000482281[/C][/ROW]
[ROW][C]175[/C][C]0.999489[/C][C]0.00102116[/C][C]0.00051058[/C][/ROW]
[ROW][C]176[/C][C]0.999903[/C][C]0.000193278[/C][C]9.66389e-05[/C][/ROW]
[ROW][C]177[/C][C]0.999868[/C][C]0.000264574[/C][C]0.000132287[/C][/ROW]
[ROW][C]178[/C][C]0.999754[/C][C]0.000491981[/C][C]0.00024599[/C][/ROW]
[ROW][C]179[/C][C]0.999318[/C][C]0.00136422[/C][C]0.000682109[/C][/ROW]
[ROW][C]180[/C][C]0.998838[/C][C]0.0023235[/C][C]0.00116175[/C][/ROW]
[ROW][C]181[/C][C]0.996956[/C][C]0.00608724[/C][C]0.00304362[/C][/ROW]
[ROW][C]182[/C][C]0.992971[/C][C]0.0140578[/C][C]0.00702889[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]185[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=5

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
93.42561e-516.85121e-511
105.05735e-681.01147e-671
115.15362e-831.03072e-821
121.75905e-963.51809e-961
133.4637e-1306.92741e-1301
148.87868e-1231.77574e-1221
155.1483e-1371.02966e-1361
16001
173.92241e-1817.84482e-1811
185.34956e-1811.06991e-1801
191.0477e-1962.09539e-1961
201.03097e-2242.06193e-2241
218.70749e-2601.7415e-2591
224.38934e-2408.77869e-2401
231.71284e-2593.42567e-2591
241.73024e-2703.46047e-2701
252.97134e-2975.94268e-2971
26001
27001
28001
29001
30001
318.06959e-091.61392e-081
321.69231e-083.38462e-081
331.66285e-083.32569e-081
346.77887e-091.35577e-081
352.49536e-094.99071e-091
369.3968e-101.87936e-091
377.24455e-071.44891e-060.999999
388.68912e-061.73782e-050.999991
390.0001123980.0002247960.999888
400.0005016910.001003380.999498
410.001658080.003316160.998342
420.0026530.005305990.997347
430.002370810.004741620.997629
440.001834190.003668390.998166
450.001382960.002765920.998617
460.001022660.002045310.998977
470.0006825680.001365140.999317
480.0005056860.001011370.999494
490.006847280.01369460.993153
500.02967310.05934620.970327
510.06957420.1391480.930426
520.116390.2327790.88361
530.1644360.3288710.835564
540.2220670.4441340.777933
550.1951670.3903340.804833
560.1700810.3401620.829919
570.1438330.2876660.856167
580.1194750.2389490.880525
590.09754180.1950840.902458
600.08895490.177910.911045
610.1480060.2960110.851994
620.1714570.3429150.828543
630.1635350.327070.836465
640.1449680.2899350.855032
650.126140.2522790.87386
660.1272340.2544680.872766
670.1079830.2159670.892017
680.09007590.1801520.909924
690.07988690.1597740.920113
700.07600660.1520130.923993
710.06538090.1307620.934619
720.05308170.1061630.946918
730.04826570.09653140.951734
740.04374230.08748460.956258
750.03525330.07050650.964747
760.02900430.05800860.970996
770.02482650.0496530.975174
780.01960170.03920330.980398
790.01495470.02990930.985045
800.01134160.02268320.988658
810.009315790.01863160.990684
820.006974810.01394960.993025
830.005323970.01064790.994676
840.004605020.009210040.995395
850.003528040.007056090.996472
860.003734880.007469750.996265
870.004546850.009093710.995453
880.003800030.007600060.9962
890.002963710.005927410.997036
900.002150510.004301020.997849
910.001577050.00315410.998423
920.001945720.003891440.998054
930.002227430.004454860.997773
940.001991340.003982670.998009
950.00177270.003545410.998227
960.002094060.004188120.997906
970.002514660.005029320.997485
980.00186340.00372680.998137
990.00139040.002780810.99861
1000.001073720.002147450.998926
1010.0007948330.001589670.999205
1020.0005882970.001176590.999412
1030.000622430.001244860.999378
1040.0007792690.001558540.999221
1050.001164280.002328550.998836
1060.00144650.0028930.998554
1070.001985420.003970840.998015
1080.002048960.004097920.997951
1090.002565150.005130290.997435
1100.002107140.004214270.997893
1110.001673080.003346160.998327
1120.003195750.00639150.996804
1130.0031710.0063420.996829
1140.00396070.00792140.996039
1150.005066570.01013310.994933
1160.004031350.00806270.995969
1170.003750880.007501760.996249
1180.002771280.005542570.997229
1190.002040860.004081720.997959
1200.001541050.00308210.998459
1210.001695350.00339070.998305
1220.001245550.00249110.998754
1230.001099410.002198810.998901
1240.001100030.002200060.9989
1250.001247230.002494460.998753
1260.00141810.002836190.998582
1270.002087220.004174440.997913
1280.003881670.007763340.996118
1290.005117490.0102350.994883
1300.004920820.009841640.995079
1310.004866410.009732810.995134
1320.004625410.009250820.995375
1330.003739530.007479060.99626
1340.00466860.00933720.995331
1350.003374480.006748950.996626
1360.002411760.004823520.997588
1370.001712770.003425550.998287
1380.001202230.002404460.998798
1390.0008632120.001726420.999137
1400.000801120.001602240.999199
1410.0005414610.001082920.999459
1420.000528650.00105730.999471
1430.000478340.000956680.999522
1440.0009568480.00191370.999043
1450.001688470.003376950.998312
1460.002271850.00454370.997728
1470.00175030.00350060.99825
1480.001216140.002432280.998784
1490.000829140.001658280.999171
1500.001186530.002373060.998813
1510.00087160.00174320.999128
1520.0008357350.001671470.999164
1530.0007105790.001421160.999289
1540.0005372260.001074450.999463
1550.0004534450.0009068910.999547
1560.000326610.0006532210.999673
1570.0003424140.0006848280.999658
1580.0002301750.000460350.99977
1590.0001765010.0003530020.999823
1600.0001831450.0003662890.999817
1610.0001947030.0003894050.999805
1620.0002172890.0004345790.999783
1630.0003315610.0006631220.999668
1640.0008326370.001665270.999167
1650.0005922790.001184560.999408
1660.0005997370.001199470.9994
1670.0007103470.001420690.99929
1680.0009163870.001832770.999084
1690.001191780.002383560.998808
1700.001698350.003396710.998302
1710.9995160.0009671040.000483552
1720.9998050.0003893930.000194697
1730.9997040.000592190.000296095
1740.9995180.0009645630.000482281
1750.9994890.001021160.00051058
1760.9999030.0001932789.66389e-05
1770.9998680.0002645740.000132287
1780.9997540.0004919810.00024599
1790.9993180.001364220.000682109
1800.9988380.00232350.00116175
1810.9969560.006087240.00304362
1820.9929710.01405780.00702889
183100
184100
185100
186100







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1400.786517NOK
5% type I error level1510.848315NOK
10% type I error level1560.876404NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 140 & 0.786517 & NOK \tabularnewline
5% type I error level & 151 & 0.848315 & NOK \tabularnewline
10% type I error level & 156 & 0.876404 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232142&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]140[/C][C]0.786517[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]151[/C][C]0.848315[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]156[/C][C]0.876404[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232142&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232142&T=6

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1400.786517NOK
5% type I error level1510.848315NOK
10% type I error level1560.876404NOK



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}