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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 computationFri, 06 Dec 2013 03:30:48 -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/06/t1386318950ytctsnqtiunsjbv.htm/, Retrieved Fri, 29 Mar 2024 14:29:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231292, Retrieved Fri, 29 Mar 2024 14:29:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [ws10] [2013-12-06 08:03:23] [a42ee995bae2f8379b6c063b00748297]
- RMP     [Multiple Regression] [ws10] [2013-12-06 08:30:48] [b11444c1beff55480dbed17c58cce579] [Current]
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Dataseries X:
1 21.033 0.02211 0.414783 0.815285
1 19.085 0.01929 0.458359 0.819521
1 20.651 0.01309 0.429895 0.825288
1 20.644 0.01353 0.434969 0.819235
1 19.649 0.01767 0.417356 0.823484
1 21.378 0.01222 0.415564 0.825069
1 24.886 0.00607 0.59604 0.764112
1 26.892 0.00344 0.63742 0.763262
1 21.812 0.0107 0.615551 0.773587
1 21.862 0.01022 0.547037 0.798463
1 21.118 0.01166 0.611137 0.776156
1 21.414 0.01141 0.58339 0.79252
1 25.703 0.00581 0.4606 0.646846
1 24.889 0.01041 0.430166 0.665833
1 24.922 0.00609 0.474791 0.654027
1 25.175 0.00839 0.565924 0.658245
1 22.333 0.01859 0.56738 0.644692
1 20.376 0.02919 0.631099 0.605417
1 17.28 0.0316 0.665318 0.719467
1 17.153 0.03365 0.649554 0.68608
1 17.536 0.03871 0.660125 0.704087
1 19.493 0.01849 0.629017 0.698951
1 22.468 0.0128 0.61906 0.679834
1 20.422 0.0184 0.537264 0.686894
1 23.831 0.01778 0.397937 0.732479
1 22.066 0.02887 0.522746 0.737948
1 25.908 0.01095 0.418622 0.720916
1 25.119 0.01328 0.358773 0.726652
1 25.97 0.00677 0.470478 0.676258
1 25.678 0.0117 0.427785 0.723797
0 26.775 0.00339 0.422229 0.741367
0 30.94 0.00167 0.432439 0.742055
0 30.775 0.00119 0.465946 0.738703
0 32.684 0.00072 0.368535 0.742133
0 33.047 0.00065 0.340068 0.741899
0 31.732 0.00135 0.344252 0.742737
1 23.216 0.00586 0.360148 0.778834
1 24.951 0.0034 0.341435 0.783626
1 26.738 0.00231 0.403884 0.766209
1 26.31 0.00265 0.396793 0.758324
1 26.822 0.00231 0.32648 0.765623
1 26.453 0.00257 0.306443 0.759203
0 22.736 0.0074 0.305062 0.654172
0 23.145 0.00675 0.457702 0.634267
0 25.368 0.00454 0.438296 0.635285
0 25.032 0.00476 0.431285 0.638928
0 24.602 0.00476 0.467489 0.631653
0 26.805 0.00432 0.610367 0.635204
0 23.162 0.00839 0.579597 0.733659
0 24.971 0.00462 0.538688 0.754073
0 25.135 0.00479 0.553134 0.775933
0 25.03 0.00474 0.507504 0.760361
0 24.692 0.00481 0.459766 0.766204
0 25.429 0.00484 0.420383 0.785714
1 21.028 0.01036 0.536009 0.819032
1 20.767 0.0118 0.558586 0.811843
1 21.422 0.00969 0.541781 0.821364
1 22.817 0.00681 0.530529 0.817756
1 22.603 0.00786 0.540049 0.813432
1 21.66 0.01143 0.547975 0.817396
0 25.554 0.00871 0.341788 0.678874
0 26.138 0.00301 0.447979 0.686264
0 25.856 0.0034 0.364867 0.694399
0 25.964 0.00351 0.25657 0.683296
0 26.415 0.003 0.27685 0.673636
0 24.547 0.0042 0.305429 0.681811
1 19.56 0.02183 0.460139 0.720908
1 19.979 0.02659 0.498133 0.729067
1 20.338 0.04882 0.513237 0.731444
1 21.718 0.02431 0.487407 0.727313
1 20.264 0.02599 0.489345 0.730387
1 18.57 0.03361 0.543299 0.733232
1 25.742 0.00442 0.495954 0.762959
1 24.178 0.00623 0.509127 0.789532
1 25.438 0.00479 0.437031 0.815908
1 25.197 0.00472 0.463514 0.807217
1 23.37 0.00905 0.489538 0.789977
1 25.82 0.0042 0.429484 0.81634
1 21.875 0.01062 0.644954 0.779612
1 19.2 0.0222 0.594387 0.790117
1 19.055 0.01823 0.544805 0.770466
1 19.659 0.01825 0.576084 0.778747
1 20.536 0.01237 0.55461 0.787896
1 22.244 0.00882 0.576644 0.772416
1 13.893 0.0547 0.556494 0.729586
1 16.176 0.02782 0.583574 0.727747
1 15.924 0.03151 0.598714 0.712199
1 13.922 0.04824 0.602874 0.740837
1 14.739 0.04214 0.599371 0.743937
1 11.866 0.07223 0.590951 0.745526
1 11.744 0.08725 0.65341 0.733165
1 19.664 0.01658 0.501037 0.71436
1 18.78 0.01914 0.454444 0.734504
1 20.969 0.01211 0.447456 0.69779
1 22.219 0.0085 0.50238 0.71217
1 21.693 0.01018 0.447285 0.705658
1 22.663 0.00852 0.366329 0.693429
1 15.338 0.08151 0.629574 0.714485
1 15.433 0.10323 0.57101 0.690892
1 12.435 0.16744 0.638545 0.674953
1 8.867 0.31482 0.671299 0.656846
1 15.06 0.11843 0.639808 0.643327
1 10.489 0.2593 0.596362 0.641418
1 26.759 0.00495 0.296888 0.722356
1 28.409 0.00243 0.263654 0.691483
1 27.421 0.00578 0.365488 0.719974
1 29.746 0.00233 0.334171 0.67793
1 26.833 0.00659 0.393563 0.700246
1 29.928 0.00238 0.311369 0.676066
1 21.934 0.00947 0.497554 0.740539
1 23.239 0.00704 0.436084 0.727863
1 22.407 0.0083 0.338097 0.712466
1 21.305 0.01316 0.498877 0.722085
1 23.671 0.0062 0.441097 0.722254
1 21.864 0.01048 0.331508 0.715121
1 23.693 0.06051 0.407701 0.662668
1 26.356 0.01554 0.450798 0.653823
1 25.69 0.01802 0.486738 0.676023
1 25.02 0.00856 0.470422 0.655239
1 24.581 0.00681 0.462516 0.58271
1 24.743 0.0235 0.487756 0.68413
1 27.166 0.01161 0.400088 0.656182
1 18.305 0.01968 0.538016 0.74148
1 18.784 0.01813 0.589956 0.732903
1 19.196 0.0202 0.618663 0.728421
1 18.857 0.01874 0.637518 0.735546
1 18.178 0.01794 0.623209 0.738245
1 18.33 0.01796 0.585169 0.736964
1 26.842 0.01724 0.457541 0.699787
1 26.369 0.00487 0.491345 0.718839
1 23.949 0.0161 0.46716 0.724045
1 26.017 0.01015 0.468621 0.735136
1 23.389 0.00903 0.470972 0.721308
1 25.619 0.00504 0.482296 0.723096
1 17.06 0.03031 0.637814 0.744064
1 17.707 0.02529 0.653427 0.706687
1 19.013 0.02278 0.6479 0.708144
1 16.747 0.0369 0.625362 0.708617
1 17.366 0.02629 0.640945 0.701404
1 18.801 0.01827 0.624811 0.696049
1 18.54 0.02485 0.677131 0.685057
1 15.648 0.04238 0.606344 0.665945
1 18.702 0.01728 0.606273 0.661735
1 18.687 0.0201 0.536102 0.632631
1 20.68 0.01049 0.49748 0.630409
1 20.366 0.01493 0.566849 0.574282
1 12.359 0.0753 0.56161 0.793509
1 14.367 0.06057 0.478024 0.768974
1 12.298 0.08069 0.55287 0.764036
1 14.989 0.07889 0.427627 0.775708
1 12.529 0.10952 0.507826 0.762726
1 8.441 0.21713 0.625866 0.76832
1 9.449 0.16265 0.584164 0.754449
1 21.52 0.04179 0.566867 0.670475
1 21.824 0.04611 0.65168 0.659333
1 22.431 0.02631 0.6283 0.652025
1 22.953 0.03191 0.611679 0.623731
1 19.075 0.10748 0.630547 0.646786
1 21.534 0.03828 0.635015 0.627337
1 19.651 0.02663 0.654945 0.675865
1 20.437 0.02073 0.653139 0.694571
1 19.388 0.0281 0.577802 0.684373
1 18.954 0.02707 0.685151 0.719576
1 21.219 0.01435 0.557045 0.673086
1 18.447 0.03882 0.671378 0.674562
0 24.078 0.0062 0.469928 0.628232
0 24.679 0.00533 0.384868 0.62671
0 21.083 0.0091 0.440988 0.628058
0 19.269 0.01337 0.372222 0.725216
0 21.02 0.00965 0.371837 0.646167
0 21.528 0.01049 0.522812 0.646818
0 26.436 0.00435 0.413295 0.7567
0 26.55 0.0043 0.36909 0.776158
0 26.547 0.00478 0.380253 0.7667
0 25.445 0.0059 0.387482 0.756482
0 26.005 0.00401 0.405991 0.761255
0 26.143 0.00415 0.361232 0.763242
1 24.151 0.0057 0.39661 0.745957
1 24.412 0.00488 0.402591 0.762508
1 23.683 0.0054 0.398499 0.778349
1 23.133 0.00611 0.352396 0.75932
1 22.866 0.00639 0.408598 0.768845
1 23.008 0.00595 0.329577 0.75718
0 23.079 0.00955 0.603515 0.669565
0 22.085 0.01179 0.663842 0.656516
0 24.199 0.00737 0.598515 0.654331
0 23.958 0.01397 0.566424 0.667654
0 25.023 0.0068 0.528485 0.663884
0 24.775 0.00703 0.555303 0.659132
0 19.368 0.04441 0.508479 0.683761
0 19.517 0.02764 0.448439 0.657899
0 19.147 0.0181 0.431674 0.683244
0 17.883 0.10715 0.407567 0.655683
0 19.02 0.07223 0.451221 0.643956
0 21.209 0.04398 0.462803 0.664357





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time22 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 22 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=231292&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]22 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=231292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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 time22 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Multiple Linear Regression - Estimated Regression Equation
status[t] = -0.362655 -0.027902HNR[t] -0.540888NHR[t] + 0.760755RPDE[t] + 1.89576DFA[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  -0.362655 -0.027902HNR[t] -0.540888NHR[t] +  0.760755RPDE[t] +  1.89576DFA[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231292&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  -0.362655 -0.027902HNR[t] -0.540888NHR[t] +  0.760755RPDE[t] +  1.89576DFA[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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] = -0.362655 -0.027902HNR[t] -0.540888NHR[t] + 0.760755RPDE[t] + 1.89576DFA[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-0.3626550.584227-0.62070.5355120.267756
HNR-0.0279020.0107456-2.5970.01015180.00507589
NHR-0.5408881.01519-0.53280.5947970.297399
RPDE0.7607550.3418812.2250.02724360.0136218
DFA1.895760.5219943.6320.000362020.00018101

\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) & -0.362655 & 0.584227 & -0.6207 & 0.535512 & 0.267756 \tabularnewline
HNR & -0.027902 & 0.0107456 & -2.597 & 0.0101518 & 0.00507589 \tabularnewline
NHR & -0.540888 & 1.01519 & -0.5328 & 0.594797 & 0.297399 \tabularnewline
RPDE & 0.760755 & 0.341881 & 2.225 & 0.0272436 & 0.0136218 \tabularnewline
DFA & 1.89576 & 0.521994 & 3.632 & 0.00036202 & 0.00018101 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231292&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]-0.362655[/C][C]0.584227[/C][C]-0.6207[/C][C]0.535512[/C][C]0.267756[/C][/ROW]
[ROW][C]HNR[/C][C]-0.027902[/C][C]0.0107456[/C][C]-2.597[/C][C]0.0101518[/C][C]0.00507589[/C][/ROW]
[ROW][C]NHR[/C][C]-0.540888[/C][C]1.01519[/C][C]-0.5328[/C][C]0.594797[/C][C]0.297399[/C][/ROW]
[ROW][C]RPDE[/C][C]0.760755[/C][C]0.341881[/C][C]2.225[/C][C]0.0272436[/C][C]0.0136218[/C][/ROW]
[ROW][C]DFA[/C][C]1.89576[/C][C]0.521994[/C][C]3.632[/C][C]0.00036202[/C][C]0.00018101[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231292&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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)-0.3626550.584227-0.62070.5355120.267756
HNR-0.0279020.0107456-2.5970.01015180.00507589
NHR-0.5408881.01519-0.53280.5947970.297399
RPDE0.7607550.3418812.2250.02724360.0136218
DFA1.895760.5219943.6320.000362020.00018101







Multiple Linear Regression - Regression Statistics
Multiple R0.454495
R-squared0.206566
Adjusted R-squared0.189862
F-TEST (value)12.3663
F-TEST (DF numerator)4
F-TEST (DF denominator)190
p-value5.86005e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.388723
Sum Squared Residuals28.7101

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.454495 \tabularnewline
R-squared & 0.206566 \tabularnewline
Adjusted R-squared & 0.189862 \tabularnewline
F-TEST (value) & 12.3663 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 190 \tabularnewline
p-value & 5.86005e-09 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.388723 \tabularnewline
Sum Squared Residuals & 28.7101 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231292&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.454495[/C][/ROW]
[ROW][C]R-squared[/C][C]0.206566[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.189862[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]12.3663[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]190[/C][/ROW]
[ROW][C]p-value[/C][C]5.86005e-09[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.388723[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]28.7101[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231292&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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 R0.454495
R-squared0.206566
Adjusted R-squared0.189862
F-TEST (value)12.3663
F-TEST (DF numerator)4
F-TEST (DF denominator)190
p-value5.86005e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.388723
Sum Squared Residuals28.7101







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.8996520.100348
210.9967110.0032886
310.9456490.054351
410.9379910.0620086
510.9581710.0418295
610.9145170.0854827
710.8417020.158298
810.8170220.182978
910.9577740.0422261
1010.9516750.0483252
1110.9781310.0218692
1210.9799210.0200795
1310.4937020.506298
1410.5267680.473232
1510.5397520.460248
1610.6087750.391225
1710.657970.34203
1810.6808590.319141
1911.00818-0.00818344
2010.9353320.064668
2110.9640870.0359125
2210.8870180.112982
2310.7632710.236729
2410.7684870.231513
2510.6541290.345871
2610.8026940.197306
2710.5936860.406314
2810.5797840.420216
2910.5490060.450994
3010.612130.38787
3100.615098-0.615098
3200.508888-0.508888
3300.532888-0.532888
3400.412274-0.412274
3500.380083-0.380083
3600.421167-0.421167
3710.7368650.263135
3810.6846340.315366
3910.6498530.350147
4010.6412690.358731
4110.5875130.412487
4210.5702540.429746
4300.47119-0.47119
4400.538516-0.538516
4500.464852-0.464852
4600.47568-0.47568
4700.501429-0.501429
4800.555626-0.555626
4900.81831-0.81831
5000.777452-0.777452
5100.825216-0.825216
5200.763938-0.763938
5300.748091-0.748091
5400.734537-0.734537
5511.00547-0.00547355
5611.01552-0.0155241
5711.00365-0.00365454
5810.9508890.0491109
5910.9553370.0446627
6010.9932620.00673753
6100.466622-0.466622
6200.548205-0.548205
6300.508056-0.508056
6400.401547-0.401547
6500.386355-0.386355
6600.475066-0.475066
6710.7964920.203508
6810.8265980.173402
6910.8205540.179446
7010.7678250.232175
7110.8147870.185213
7210.9043710.0956289
7310.7403840.259616
7410.8434410.156559
7510.8042180.195782
7610.8146510.185349
7710.8504010.149599
7810.7889560.211044
7910.989850.0101503
8011.03967-0.0396699
8110.970890.0291102
8210.9935210.00647944
8310.9732390.0267613
8410.9149180.0850816
8511.02659-0.0265877
8610.9945410.00545852
8710.981620.0183805
8811.08589-0.0858857
8911.0696-0.0696011
9011.1301-0.130095
9111.14946-0.149458
9210.815130.18487
9310.8411530.158847
9410.7089610.291039
9510.7450810.254919
9610.7045890.295411
9710.5936520.406348
9810.9987360.00126368
9910.8950580.104942
10010.9651390.0348609
10110.9755690.0244313
10210.8594110.140589
10310.8740850.125915
10410.4833070.516693
10510.3548210.645179
10610.5120590.487941
10710.3455230.654477
10810.5119860.488014
10910.3195370.680463
11010.8026170.197383
11110.6967250.303275
11210.6155250.384475
11310.7841940.215806
11410.6783060.321694
11510.6295180.370482
11610.509950.49005
11710.4759890.524011
11810.5626580.437342
11910.5346550.465345
12010.4043390.595661
12110.602260.39774
12210.4214090.578591
12310.9309170.0690831
12410.9416440.0583561
12510.9423710.0576291
12610.9804710.0195294
12710.994080.00592018
12810.958460.0415397
12910.5537760.446224
13010.6354990.364501
13110.6884180.311582
13210.6560720.343928
13310.7055780.294422
13410.6575190.342481
13511.04073-0.0407257
13610.9664080.0335916
13710.9298830.0701166
13810.9692230.0307772
13910.9558710.0441289
14010.8977440.102256
14110.9204320.0795682
14210.9015590.0984407
14310.8218880.178112
14410.7122240.287776
14510.6282190.371781
14610.5809480.419052
14711.18332-0.183322
14811.02516-0.0251607
14911.11959-0.119586
15010.9723230.0276772
15111.0608-0.0607955
15211.21706-0.217058
15311.16038-0.16038
15410.7165930.283407
15510.7491740.250826
15610.7113060.288694
15710.627430.37257
15810.7528190.247181
15910.6881660.311834
16010.8541660.145834
16110.8695140.130486
16210.8181510.181849
16310.979220.0207796
16410.7373110.262689
16510.8911980.108802
16600.510641-0.510641
16700.426747-0.426747
16800.570293-0.570293
16900.750471-0.750471
17000.553476-0.553476
17100.654937-0.654937
17200.646309-0.646309
17300.646413-0.646413
17400.6368-0.6368
17500.653071-0.653071
17600.661597-0.661597
17700.627387-0.627387
17810.6762750.323725
17910.7053630.294637
18010.752340.24766
18110.6961550.303845
18210.7642660.235734
18310.6783120.321688
18400.716687-0.716687
18500.764367-0.764367
18600.653933-0.653933
18700.657931-0.657931
18800.596084-0.596084
18900.614273-0.614273
19000.755989-0.755989
19100.666199-0.666199
19200.716977-0.716977
19300.63349-0.63349
19400.631632-0.631632
19500.633321-0.633321

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.899652 & 0.100348 \tabularnewline
2 & 1 & 0.996711 & 0.0032886 \tabularnewline
3 & 1 & 0.945649 & 0.054351 \tabularnewline
4 & 1 & 0.937991 & 0.0620086 \tabularnewline
5 & 1 & 0.958171 & 0.0418295 \tabularnewline
6 & 1 & 0.914517 & 0.0854827 \tabularnewline
7 & 1 & 0.841702 & 0.158298 \tabularnewline
8 & 1 & 0.817022 & 0.182978 \tabularnewline
9 & 1 & 0.957774 & 0.0422261 \tabularnewline
10 & 1 & 0.951675 & 0.0483252 \tabularnewline
11 & 1 & 0.978131 & 0.0218692 \tabularnewline
12 & 1 & 0.979921 & 0.0200795 \tabularnewline
13 & 1 & 0.493702 & 0.506298 \tabularnewline
14 & 1 & 0.526768 & 0.473232 \tabularnewline
15 & 1 & 0.539752 & 0.460248 \tabularnewline
16 & 1 & 0.608775 & 0.391225 \tabularnewline
17 & 1 & 0.65797 & 0.34203 \tabularnewline
18 & 1 & 0.680859 & 0.319141 \tabularnewline
19 & 1 & 1.00818 & -0.00818344 \tabularnewline
20 & 1 & 0.935332 & 0.064668 \tabularnewline
21 & 1 & 0.964087 & 0.0359125 \tabularnewline
22 & 1 & 0.887018 & 0.112982 \tabularnewline
23 & 1 & 0.763271 & 0.236729 \tabularnewline
24 & 1 & 0.768487 & 0.231513 \tabularnewline
25 & 1 & 0.654129 & 0.345871 \tabularnewline
26 & 1 & 0.802694 & 0.197306 \tabularnewline
27 & 1 & 0.593686 & 0.406314 \tabularnewline
28 & 1 & 0.579784 & 0.420216 \tabularnewline
29 & 1 & 0.549006 & 0.450994 \tabularnewline
30 & 1 & 0.61213 & 0.38787 \tabularnewline
31 & 0 & 0.615098 & -0.615098 \tabularnewline
32 & 0 & 0.508888 & -0.508888 \tabularnewline
33 & 0 & 0.532888 & -0.532888 \tabularnewline
34 & 0 & 0.412274 & -0.412274 \tabularnewline
35 & 0 & 0.380083 & -0.380083 \tabularnewline
36 & 0 & 0.421167 & -0.421167 \tabularnewline
37 & 1 & 0.736865 & 0.263135 \tabularnewline
38 & 1 & 0.684634 & 0.315366 \tabularnewline
39 & 1 & 0.649853 & 0.350147 \tabularnewline
40 & 1 & 0.641269 & 0.358731 \tabularnewline
41 & 1 & 0.587513 & 0.412487 \tabularnewline
42 & 1 & 0.570254 & 0.429746 \tabularnewline
43 & 0 & 0.47119 & -0.47119 \tabularnewline
44 & 0 & 0.538516 & -0.538516 \tabularnewline
45 & 0 & 0.464852 & -0.464852 \tabularnewline
46 & 0 & 0.47568 & -0.47568 \tabularnewline
47 & 0 & 0.501429 & -0.501429 \tabularnewline
48 & 0 & 0.555626 & -0.555626 \tabularnewline
49 & 0 & 0.81831 & -0.81831 \tabularnewline
50 & 0 & 0.777452 & -0.777452 \tabularnewline
51 & 0 & 0.825216 & -0.825216 \tabularnewline
52 & 0 & 0.763938 & -0.763938 \tabularnewline
53 & 0 & 0.748091 & -0.748091 \tabularnewline
54 & 0 & 0.734537 & -0.734537 \tabularnewline
55 & 1 & 1.00547 & -0.00547355 \tabularnewline
56 & 1 & 1.01552 & -0.0155241 \tabularnewline
57 & 1 & 1.00365 & -0.00365454 \tabularnewline
58 & 1 & 0.950889 & 0.0491109 \tabularnewline
59 & 1 & 0.955337 & 0.0446627 \tabularnewline
60 & 1 & 0.993262 & 0.00673753 \tabularnewline
61 & 0 & 0.466622 & -0.466622 \tabularnewline
62 & 0 & 0.548205 & -0.548205 \tabularnewline
63 & 0 & 0.508056 & -0.508056 \tabularnewline
64 & 0 & 0.401547 & -0.401547 \tabularnewline
65 & 0 & 0.386355 & -0.386355 \tabularnewline
66 & 0 & 0.475066 & -0.475066 \tabularnewline
67 & 1 & 0.796492 & 0.203508 \tabularnewline
68 & 1 & 0.826598 & 0.173402 \tabularnewline
69 & 1 & 0.820554 & 0.179446 \tabularnewline
70 & 1 & 0.767825 & 0.232175 \tabularnewline
71 & 1 & 0.814787 & 0.185213 \tabularnewline
72 & 1 & 0.904371 & 0.0956289 \tabularnewline
73 & 1 & 0.740384 & 0.259616 \tabularnewline
74 & 1 & 0.843441 & 0.156559 \tabularnewline
75 & 1 & 0.804218 & 0.195782 \tabularnewline
76 & 1 & 0.814651 & 0.185349 \tabularnewline
77 & 1 & 0.850401 & 0.149599 \tabularnewline
78 & 1 & 0.788956 & 0.211044 \tabularnewline
79 & 1 & 0.98985 & 0.0101503 \tabularnewline
80 & 1 & 1.03967 & -0.0396699 \tabularnewline
81 & 1 & 0.97089 & 0.0291102 \tabularnewline
82 & 1 & 0.993521 & 0.00647944 \tabularnewline
83 & 1 & 0.973239 & 0.0267613 \tabularnewline
84 & 1 & 0.914918 & 0.0850816 \tabularnewline
85 & 1 & 1.02659 & -0.0265877 \tabularnewline
86 & 1 & 0.994541 & 0.00545852 \tabularnewline
87 & 1 & 0.98162 & 0.0183805 \tabularnewline
88 & 1 & 1.08589 & -0.0858857 \tabularnewline
89 & 1 & 1.0696 & -0.0696011 \tabularnewline
90 & 1 & 1.1301 & -0.130095 \tabularnewline
91 & 1 & 1.14946 & -0.149458 \tabularnewline
92 & 1 & 0.81513 & 0.18487 \tabularnewline
93 & 1 & 0.841153 & 0.158847 \tabularnewline
94 & 1 & 0.708961 & 0.291039 \tabularnewline
95 & 1 & 0.745081 & 0.254919 \tabularnewline
96 & 1 & 0.704589 & 0.295411 \tabularnewline
97 & 1 & 0.593652 & 0.406348 \tabularnewline
98 & 1 & 0.998736 & 0.00126368 \tabularnewline
99 & 1 & 0.895058 & 0.104942 \tabularnewline
100 & 1 & 0.965139 & 0.0348609 \tabularnewline
101 & 1 & 0.975569 & 0.0244313 \tabularnewline
102 & 1 & 0.859411 & 0.140589 \tabularnewline
103 & 1 & 0.874085 & 0.125915 \tabularnewline
104 & 1 & 0.483307 & 0.516693 \tabularnewline
105 & 1 & 0.354821 & 0.645179 \tabularnewline
106 & 1 & 0.512059 & 0.487941 \tabularnewline
107 & 1 & 0.345523 & 0.654477 \tabularnewline
108 & 1 & 0.511986 & 0.488014 \tabularnewline
109 & 1 & 0.319537 & 0.680463 \tabularnewline
110 & 1 & 0.802617 & 0.197383 \tabularnewline
111 & 1 & 0.696725 & 0.303275 \tabularnewline
112 & 1 & 0.615525 & 0.384475 \tabularnewline
113 & 1 & 0.784194 & 0.215806 \tabularnewline
114 & 1 & 0.678306 & 0.321694 \tabularnewline
115 & 1 & 0.629518 & 0.370482 \tabularnewline
116 & 1 & 0.50995 & 0.49005 \tabularnewline
117 & 1 & 0.475989 & 0.524011 \tabularnewline
118 & 1 & 0.562658 & 0.437342 \tabularnewline
119 & 1 & 0.534655 & 0.465345 \tabularnewline
120 & 1 & 0.404339 & 0.595661 \tabularnewline
121 & 1 & 0.60226 & 0.39774 \tabularnewline
122 & 1 & 0.421409 & 0.578591 \tabularnewline
123 & 1 & 0.930917 & 0.0690831 \tabularnewline
124 & 1 & 0.941644 & 0.0583561 \tabularnewline
125 & 1 & 0.942371 & 0.0576291 \tabularnewline
126 & 1 & 0.980471 & 0.0195294 \tabularnewline
127 & 1 & 0.99408 & 0.00592018 \tabularnewline
128 & 1 & 0.95846 & 0.0415397 \tabularnewline
129 & 1 & 0.553776 & 0.446224 \tabularnewline
130 & 1 & 0.635499 & 0.364501 \tabularnewline
131 & 1 & 0.688418 & 0.311582 \tabularnewline
132 & 1 & 0.656072 & 0.343928 \tabularnewline
133 & 1 & 0.705578 & 0.294422 \tabularnewline
134 & 1 & 0.657519 & 0.342481 \tabularnewline
135 & 1 & 1.04073 & -0.0407257 \tabularnewline
136 & 1 & 0.966408 & 0.0335916 \tabularnewline
137 & 1 & 0.929883 & 0.0701166 \tabularnewline
138 & 1 & 0.969223 & 0.0307772 \tabularnewline
139 & 1 & 0.955871 & 0.0441289 \tabularnewline
140 & 1 & 0.897744 & 0.102256 \tabularnewline
141 & 1 & 0.920432 & 0.0795682 \tabularnewline
142 & 1 & 0.901559 & 0.0984407 \tabularnewline
143 & 1 & 0.821888 & 0.178112 \tabularnewline
144 & 1 & 0.712224 & 0.287776 \tabularnewline
145 & 1 & 0.628219 & 0.371781 \tabularnewline
146 & 1 & 0.580948 & 0.419052 \tabularnewline
147 & 1 & 1.18332 & -0.183322 \tabularnewline
148 & 1 & 1.02516 & -0.0251607 \tabularnewline
149 & 1 & 1.11959 & -0.119586 \tabularnewline
150 & 1 & 0.972323 & 0.0276772 \tabularnewline
151 & 1 & 1.0608 & -0.0607955 \tabularnewline
152 & 1 & 1.21706 & -0.217058 \tabularnewline
153 & 1 & 1.16038 & -0.16038 \tabularnewline
154 & 1 & 0.716593 & 0.283407 \tabularnewline
155 & 1 & 0.749174 & 0.250826 \tabularnewline
156 & 1 & 0.711306 & 0.288694 \tabularnewline
157 & 1 & 0.62743 & 0.37257 \tabularnewline
158 & 1 & 0.752819 & 0.247181 \tabularnewline
159 & 1 & 0.688166 & 0.311834 \tabularnewline
160 & 1 & 0.854166 & 0.145834 \tabularnewline
161 & 1 & 0.869514 & 0.130486 \tabularnewline
162 & 1 & 0.818151 & 0.181849 \tabularnewline
163 & 1 & 0.97922 & 0.0207796 \tabularnewline
164 & 1 & 0.737311 & 0.262689 \tabularnewline
165 & 1 & 0.891198 & 0.108802 \tabularnewline
166 & 0 & 0.510641 & -0.510641 \tabularnewline
167 & 0 & 0.426747 & -0.426747 \tabularnewline
168 & 0 & 0.570293 & -0.570293 \tabularnewline
169 & 0 & 0.750471 & -0.750471 \tabularnewline
170 & 0 & 0.553476 & -0.553476 \tabularnewline
171 & 0 & 0.654937 & -0.654937 \tabularnewline
172 & 0 & 0.646309 & -0.646309 \tabularnewline
173 & 0 & 0.646413 & -0.646413 \tabularnewline
174 & 0 & 0.6368 & -0.6368 \tabularnewline
175 & 0 & 0.653071 & -0.653071 \tabularnewline
176 & 0 & 0.661597 & -0.661597 \tabularnewline
177 & 0 & 0.627387 & -0.627387 \tabularnewline
178 & 1 & 0.676275 & 0.323725 \tabularnewline
179 & 1 & 0.705363 & 0.294637 \tabularnewline
180 & 1 & 0.75234 & 0.24766 \tabularnewline
181 & 1 & 0.696155 & 0.303845 \tabularnewline
182 & 1 & 0.764266 & 0.235734 \tabularnewline
183 & 1 & 0.678312 & 0.321688 \tabularnewline
184 & 0 & 0.716687 & -0.716687 \tabularnewline
185 & 0 & 0.764367 & -0.764367 \tabularnewline
186 & 0 & 0.653933 & -0.653933 \tabularnewline
187 & 0 & 0.657931 & -0.657931 \tabularnewline
188 & 0 & 0.596084 & -0.596084 \tabularnewline
189 & 0 & 0.614273 & -0.614273 \tabularnewline
190 & 0 & 0.755989 & -0.755989 \tabularnewline
191 & 0 & 0.666199 & -0.666199 \tabularnewline
192 & 0 & 0.716977 & -0.716977 \tabularnewline
193 & 0 & 0.63349 & -0.63349 \tabularnewline
194 & 0 & 0.631632 & -0.631632 \tabularnewline
195 & 0 & 0.633321 & -0.633321 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231292&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]0.899652[/C][C]0.100348[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.996711[/C][C]0.0032886[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.945649[/C][C]0.054351[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.937991[/C][C]0.0620086[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.958171[/C][C]0.0418295[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.914517[/C][C]0.0854827[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.841702[/C][C]0.158298[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.817022[/C][C]0.182978[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.957774[/C][C]0.0422261[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.951675[/C][C]0.0483252[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.978131[/C][C]0.0218692[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.979921[/C][C]0.0200795[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.493702[/C][C]0.506298[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.526768[/C][C]0.473232[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.539752[/C][C]0.460248[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.608775[/C][C]0.391225[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.65797[/C][C]0.34203[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.680859[/C][C]0.319141[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.00818[/C][C]-0.00818344[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.935332[/C][C]0.064668[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.964087[/C][C]0.0359125[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.887018[/C][C]0.112982[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.763271[/C][C]0.236729[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.768487[/C][C]0.231513[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.654129[/C][C]0.345871[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.802694[/C][C]0.197306[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.593686[/C][C]0.406314[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.579784[/C][C]0.420216[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.549006[/C][C]0.450994[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.61213[/C][C]0.38787[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.615098[/C][C]-0.615098[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.508888[/C][C]-0.508888[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.532888[/C][C]-0.532888[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.412274[/C][C]-0.412274[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.380083[/C][C]-0.380083[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.421167[/C][C]-0.421167[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.736865[/C][C]0.263135[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.684634[/C][C]0.315366[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.649853[/C][C]0.350147[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.641269[/C][C]0.358731[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.587513[/C][C]0.412487[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.570254[/C][C]0.429746[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.47119[/C][C]-0.47119[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.538516[/C][C]-0.538516[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.464852[/C][C]-0.464852[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.47568[/C][C]-0.47568[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.501429[/C][C]-0.501429[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0.555626[/C][C]-0.555626[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.81831[/C][C]-0.81831[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.777452[/C][C]-0.777452[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.825216[/C][C]-0.825216[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.763938[/C][C]-0.763938[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.748091[/C][C]-0.748091[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.734537[/C][C]-0.734537[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]1.00547[/C][C]-0.00547355[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]1.01552[/C][C]-0.0155241[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]1.00365[/C][C]-0.00365454[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.950889[/C][C]0.0491109[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.955337[/C][C]0.0446627[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.993262[/C][C]0.00673753[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.466622[/C][C]-0.466622[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.548205[/C][C]-0.548205[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.508056[/C][C]-0.508056[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.401547[/C][C]-0.401547[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.386355[/C][C]-0.386355[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.475066[/C][C]-0.475066[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.796492[/C][C]0.203508[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.826598[/C][C]0.173402[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.820554[/C][C]0.179446[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.767825[/C][C]0.232175[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.814787[/C][C]0.185213[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]0.904371[/C][C]0.0956289[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.740384[/C][C]0.259616[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.843441[/C][C]0.156559[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.804218[/C][C]0.195782[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.814651[/C][C]0.185349[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.850401[/C][C]0.149599[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.788956[/C][C]0.211044[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.98985[/C][C]0.0101503[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]1.03967[/C][C]-0.0396699[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]0.97089[/C][C]0.0291102[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]0.993521[/C][C]0.00647944[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.973239[/C][C]0.0267613[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.914918[/C][C]0.0850816[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]1.02659[/C][C]-0.0265877[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.994541[/C][C]0.00545852[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.98162[/C][C]0.0183805[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]1.08589[/C][C]-0.0858857[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]1.0696[/C][C]-0.0696011[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]1.1301[/C][C]-0.130095[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.14946[/C][C]-0.149458[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.81513[/C][C]0.18487[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.841153[/C][C]0.158847[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.708961[/C][C]0.291039[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.745081[/C][C]0.254919[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.704589[/C][C]0.295411[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.593652[/C][C]0.406348[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.998736[/C][C]0.00126368[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.895058[/C][C]0.104942[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.965139[/C][C]0.0348609[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.975569[/C][C]0.0244313[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.859411[/C][C]0.140589[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]0.874085[/C][C]0.125915[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.483307[/C][C]0.516693[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.354821[/C][C]0.645179[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.512059[/C][C]0.487941[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.345523[/C][C]0.654477[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.511986[/C][C]0.488014[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.319537[/C][C]0.680463[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.802617[/C][C]0.197383[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.696725[/C][C]0.303275[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.615525[/C][C]0.384475[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.784194[/C][C]0.215806[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.678306[/C][C]0.321694[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.629518[/C][C]0.370482[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.50995[/C][C]0.49005[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.475989[/C][C]0.524011[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.562658[/C][C]0.437342[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.534655[/C][C]0.465345[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.404339[/C][C]0.595661[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.60226[/C][C]0.39774[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.421409[/C][C]0.578591[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.930917[/C][C]0.0690831[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.941644[/C][C]0.0583561[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.942371[/C][C]0.0576291[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.980471[/C][C]0.0195294[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.99408[/C][C]0.00592018[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.95846[/C][C]0.0415397[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.553776[/C][C]0.446224[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.635499[/C][C]0.364501[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.688418[/C][C]0.311582[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.656072[/C][C]0.343928[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.705578[/C][C]0.294422[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.657519[/C][C]0.342481[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]1.04073[/C][C]-0.0407257[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.966408[/C][C]0.0335916[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.929883[/C][C]0.0701166[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.969223[/C][C]0.0307772[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.955871[/C][C]0.0441289[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.897744[/C][C]0.102256[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.920432[/C][C]0.0795682[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.901559[/C][C]0.0984407[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.821888[/C][C]0.178112[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.712224[/C][C]0.287776[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.628219[/C][C]0.371781[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.580948[/C][C]0.419052[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.18332[/C][C]-0.183322[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]1.02516[/C][C]-0.0251607[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.11959[/C][C]-0.119586[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.972323[/C][C]0.0276772[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]1.0608[/C][C]-0.0607955[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]1.21706[/C][C]-0.217058[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]1.16038[/C][C]-0.16038[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.716593[/C][C]0.283407[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.749174[/C][C]0.250826[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.711306[/C][C]0.288694[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.62743[/C][C]0.37257[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.752819[/C][C]0.247181[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.688166[/C][C]0.311834[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.854166[/C][C]0.145834[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]0.869514[/C][C]0.130486[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.818151[/C][C]0.181849[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.97922[/C][C]0.0207796[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.737311[/C][C]0.262689[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.891198[/C][C]0.108802[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.510641[/C][C]-0.510641[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.426747[/C][C]-0.426747[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.570293[/C][C]-0.570293[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.750471[/C][C]-0.750471[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.553476[/C][C]-0.553476[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.654937[/C][C]-0.654937[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.646309[/C][C]-0.646309[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.646413[/C][C]-0.646413[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.6368[/C][C]-0.6368[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.653071[/C][C]-0.653071[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.661597[/C][C]-0.661597[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.627387[/C][C]-0.627387[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.676275[/C][C]0.323725[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.705363[/C][C]0.294637[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.75234[/C][C]0.24766[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.696155[/C][C]0.303845[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.764266[/C][C]0.235734[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.678312[/C][C]0.321688[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.716687[/C][C]-0.716687[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.764367[/C][C]-0.764367[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.653933[/C][C]-0.653933[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.657931[/C][C]-0.657931[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.596084[/C][C]-0.596084[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.614273[/C][C]-0.614273[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.755989[/C][C]-0.755989[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.666199[/C][C]-0.666199[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.716977[/C][C]-0.716977[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.63349[/C][C]-0.63349[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.631632[/C][C]-0.631632[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.633321[/C][C]-0.633321[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231292&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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
110.8996520.100348
210.9967110.0032886
310.9456490.054351
410.9379910.0620086
510.9581710.0418295
610.9145170.0854827
710.8417020.158298
810.8170220.182978
910.9577740.0422261
1010.9516750.0483252
1110.9781310.0218692
1210.9799210.0200795
1310.4937020.506298
1410.5267680.473232
1510.5397520.460248
1610.6087750.391225
1710.657970.34203
1810.6808590.319141
1911.00818-0.00818344
2010.9353320.064668
2110.9640870.0359125
2210.8870180.112982
2310.7632710.236729
2410.7684870.231513
2510.6541290.345871
2610.8026940.197306
2710.5936860.406314
2810.5797840.420216
2910.5490060.450994
3010.612130.38787
3100.615098-0.615098
3200.508888-0.508888
3300.532888-0.532888
3400.412274-0.412274
3500.380083-0.380083
3600.421167-0.421167
3710.7368650.263135
3810.6846340.315366
3910.6498530.350147
4010.6412690.358731
4110.5875130.412487
4210.5702540.429746
4300.47119-0.47119
4400.538516-0.538516
4500.464852-0.464852
4600.47568-0.47568
4700.501429-0.501429
4800.555626-0.555626
4900.81831-0.81831
5000.777452-0.777452
5100.825216-0.825216
5200.763938-0.763938
5300.748091-0.748091
5400.734537-0.734537
5511.00547-0.00547355
5611.01552-0.0155241
5711.00365-0.00365454
5810.9508890.0491109
5910.9553370.0446627
6010.9932620.00673753
6100.466622-0.466622
6200.548205-0.548205
6300.508056-0.508056
6400.401547-0.401547
6500.386355-0.386355
6600.475066-0.475066
6710.7964920.203508
6810.8265980.173402
6910.8205540.179446
7010.7678250.232175
7110.8147870.185213
7210.9043710.0956289
7310.7403840.259616
7410.8434410.156559
7510.8042180.195782
7610.8146510.185349
7710.8504010.149599
7810.7889560.211044
7910.989850.0101503
8011.03967-0.0396699
8110.970890.0291102
8210.9935210.00647944
8310.9732390.0267613
8410.9149180.0850816
8511.02659-0.0265877
8610.9945410.00545852
8710.981620.0183805
8811.08589-0.0858857
8911.0696-0.0696011
9011.1301-0.130095
9111.14946-0.149458
9210.815130.18487
9310.8411530.158847
9410.7089610.291039
9510.7450810.254919
9610.7045890.295411
9710.5936520.406348
9810.9987360.00126368
9910.8950580.104942
10010.9651390.0348609
10110.9755690.0244313
10210.8594110.140589
10310.8740850.125915
10410.4833070.516693
10510.3548210.645179
10610.5120590.487941
10710.3455230.654477
10810.5119860.488014
10910.3195370.680463
11010.8026170.197383
11110.6967250.303275
11210.6155250.384475
11310.7841940.215806
11410.6783060.321694
11510.6295180.370482
11610.509950.49005
11710.4759890.524011
11810.5626580.437342
11910.5346550.465345
12010.4043390.595661
12110.602260.39774
12210.4214090.578591
12310.9309170.0690831
12410.9416440.0583561
12510.9423710.0576291
12610.9804710.0195294
12710.994080.00592018
12810.958460.0415397
12910.5537760.446224
13010.6354990.364501
13110.6884180.311582
13210.6560720.343928
13310.7055780.294422
13410.6575190.342481
13511.04073-0.0407257
13610.9664080.0335916
13710.9298830.0701166
13810.9692230.0307772
13910.9558710.0441289
14010.8977440.102256
14110.9204320.0795682
14210.9015590.0984407
14310.8218880.178112
14410.7122240.287776
14510.6282190.371781
14610.5809480.419052
14711.18332-0.183322
14811.02516-0.0251607
14911.11959-0.119586
15010.9723230.0276772
15111.0608-0.0607955
15211.21706-0.217058
15311.16038-0.16038
15410.7165930.283407
15510.7491740.250826
15610.7113060.288694
15710.627430.37257
15810.7528190.247181
15910.6881660.311834
16010.8541660.145834
16110.8695140.130486
16210.8181510.181849
16310.979220.0207796
16410.7373110.262689
16510.8911980.108802
16600.510641-0.510641
16700.426747-0.426747
16800.570293-0.570293
16900.750471-0.750471
17000.553476-0.553476
17100.654937-0.654937
17200.646309-0.646309
17300.646413-0.646413
17400.6368-0.6368
17500.653071-0.653071
17600.661597-0.661597
17700.627387-0.627387
17810.6762750.323725
17910.7053630.294637
18010.752340.24766
18110.6961550.303845
18210.7642660.235734
18310.6783120.321688
18400.716687-0.716687
18500.764367-0.764367
18600.653933-0.653933
18700.657931-0.657931
18800.596084-0.596084
18900.614273-0.614273
19000.755989-0.755989
19100.666199-0.666199
19200.716977-0.716977
19300.63349-0.63349
19400.631632-0.631632
19500.633321-0.633321







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
84.39888e-488.79776e-481
95.6114e-651.12228e-641
108.3199e-811.66398e-801
111.20902e-942.41803e-941
122.83547e-1075.67094e-1071
139.17441e-1431.83488e-1421
141.88764e-1403.77528e-1401
151.12319e-1542.24637e-1541
16001
174.49195e-2008.98391e-2001
182.64057e-1985.28115e-1981
192.80252e-2145.60503e-2141
209.74994e-2441.94999e-2431
219.48401e-2801.8968e-2791
221.76907e-2573.53814e-2571
233.61254e-2777.22507e-2771
245.11939e-2881.02388e-2871
257.30300000047781e-3151.46060000009556e-3141
26001
27001
28001
29001
30001
319.51424e-061.90285e-050.99999
320.0002169860.0004339720.999783
330.0005043140.001008630.999496
340.0003978790.0007957580.999602
350.0002645540.0005291080.999735
360.000220370.000440740.99978
370.0001231930.0002463870.999877
387.94036e-050.0001588070.999921
398.37099e-050.000167420.999916
406.77279e-050.0001354560.999932
415.76946e-050.0001153890.999942
424.05859e-058.11719e-050.999959
430.00886140.01772280.991139
440.04314180.08628360.956858
450.06896360.1379270.931036
460.0938280.1876560.906172
470.118190.236380.88181
480.1373010.2746010.862699
490.2632950.5265910.736705
500.3738330.7476660.626167
510.4998880.9997770.500112
520.6015410.7969190.398459
530.6975830.6048350.302417
540.7812080.4375840.218792
550.7474820.5050360.252518
560.7107380.5785250.289262
570.6731650.653670.326835
580.6398710.7202580.360129
590.6033850.7932290.396615
600.5607320.8785350.439268
610.5945060.8109880.405494
620.6200470.7599070.379953
630.6407060.7185880.359294
640.6393130.7213730.360687
650.6312720.7374560.368728
660.640190.719620.35981
670.6033960.7932080.396604
680.5642040.8715930.435796
690.5512140.8975710.448786
700.5130060.9739870.486994
710.4727550.945510.527245
720.4375890.8751770.562411
730.4303790.8607590.569621
740.4010250.802050.598975
750.3750120.7500240.624988
760.3484270.6968540.651573
770.3154260.6308530.684574
780.2915570.5831140.708443
790.2564240.5128480.743576
800.2283460.4566920.771654
810.1980430.3960860.801957
820.1704130.3408270.829587
830.1447950.289590.855205
840.1238380.2476770.876162
850.1263770.2527530.873623
860.1077420.2154850.892258
870.0913410.1826820.908659
880.08593210.1718640.914068
890.07598440.1519690.924016
900.07631360.1526270.923686
910.07110410.1422080.928896
920.06117220.1223440.938828
930.05162410.1032480.948376
940.04782720.09565440.952173
950.04260440.08520880.957396
960.03915670.07831340.960843
970.04071810.08143620.959282
980.03246980.06493960.96753
990.02620950.05241910.97379
1000.0205350.04106990.979465
1010.01597660.03195330.984023
1020.01269560.02539120.987304
1030.009833440.01966690.990167
1040.01231680.02463370.987683
1050.01969250.0393850.980308
1060.02253760.04507520.977462
1070.03475730.06951460.965243
1080.03913260.07826520.960867
1090.0605160.1210320.939484
1100.05160930.1032190.948391
1110.04748220.09496450.952518
1120.04930880.09861750.950691
1130.04261370.08522740.957386
1140.04028090.08056180.959719
1150.04374650.08749290.956254
1160.05235610.1047120.947644
1170.0655990.1311980.934401
1180.07177530.1435510.928225
1190.08325830.1665170.916742
1200.1262950.2525890.873705
1210.135880.2717590.86412
1220.2111680.4223360.788832
1230.1824560.3649130.817544
1240.1553580.3107160.844642
1250.1311030.2622060.868897
1260.1102620.2205240.889738
1270.0918960.1837920.908104
1280.0752130.1504260.924787
1290.09690070.1938010.903099
1300.1057050.2114110.894295
1310.1115280.2230560.888472
1320.1267840.2535690.873216
1330.1332060.2664110.866794
1340.1559540.3119080.844046
1350.1341230.2682460.865877
1360.1119860.2239720.888014
1370.09200640.1840130.907994
1380.07488920.1497780.925111
1390.06037110.1207420.939629
1400.04797420.09594840.952026
1410.03768540.07537070.962315
1420.02928890.05857780.970711
1430.02335120.04670230.976649
1440.0230510.0461020.976949
1450.03131930.06263870.968681
1460.05408040.1081610.94592
1470.04898240.09796470.951018
1480.03846050.07692110.961539
1490.03150020.06300040.9685
1500.02501310.05002620.974987
1510.01890670.03781330.981093
1520.01758720.03517440.982413
1530.02076380.04152760.979236
1540.02188890.04377790.978111
1550.02013050.04026090.97987
1560.02391980.04783960.97608
1570.05682660.1136530.943173
1580.07682880.1536580.923171
1590.1845180.3690370.815482
1600.1726770.3453540.827323
1610.1571150.3142310.842885
1620.1640910.3281820.835909
1630.1324050.264810.867595
1640.2144660.4289320.785534
1650.3109430.6218850.689057
1660.3093640.6187280.690636
1670.3276860.6553730.672314
1680.3165320.6330630.683468
1690.5583780.8832430.441622
1700.5204770.9590460.479523
1710.4884710.9769420.511529
1720.4811610.9623220.518839
1730.533130.933740.46687
1740.5926210.8147590.407379
1750.7128590.5742820.287141
1760.8973060.2053880.102694
1770.999991.90183e-059.50914e-06
1780.9999892.2361e-051.11805e-05
1790.9999617.72862e-053.86431e-05
1800.9999060.0001879849.39922e-05
1810.9997150.0005694360.000284718
1820.9990710.001857830.000928914
183100
184100
185100
186100
187100

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 4.39888e-48 & 8.79776e-48 & 1 \tabularnewline
9 & 5.6114e-65 & 1.12228e-64 & 1 \tabularnewline
10 & 8.3199e-81 & 1.66398e-80 & 1 \tabularnewline
11 & 1.20902e-94 & 2.41803e-94 & 1 \tabularnewline
12 & 2.83547e-107 & 5.67094e-107 & 1 \tabularnewline
13 & 9.17441e-143 & 1.83488e-142 & 1 \tabularnewline
14 & 1.88764e-140 & 3.77528e-140 & 1 \tabularnewline
15 & 1.12319e-154 & 2.24637e-154 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 4.49195e-200 & 8.98391e-200 & 1 \tabularnewline
18 & 2.64057e-198 & 5.28115e-198 & 1 \tabularnewline
19 & 2.80252e-214 & 5.60503e-214 & 1 \tabularnewline
20 & 9.74994e-244 & 1.94999e-243 & 1 \tabularnewline
21 & 9.48401e-280 & 1.8968e-279 & 1 \tabularnewline
22 & 1.76907e-257 & 3.53814e-257 & 1 \tabularnewline
23 & 3.61254e-277 & 7.22507e-277 & 1 \tabularnewline
24 & 5.11939e-288 & 1.02388e-287 & 1 \tabularnewline
25 & 7.30300000047781e-315 & 1.46060000009556e-314 & 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 & 9.51424e-06 & 1.90285e-05 & 0.99999 \tabularnewline
32 & 0.000216986 & 0.000433972 & 0.999783 \tabularnewline
33 & 0.000504314 & 0.00100863 & 0.999496 \tabularnewline
34 & 0.000397879 & 0.000795758 & 0.999602 \tabularnewline
35 & 0.000264554 & 0.000529108 & 0.999735 \tabularnewline
36 & 0.00022037 & 0.00044074 & 0.99978 \tabularnewline
37 & 0.000123193 & 0.000246387 & 0.999877 \tabularnewline
38 & 7.94036e-05 & 0.000158807 & 0.999921 \tabularnewline
39 & 8.37099e-05 & 0.00016742 & 0.999916 \tabularnewline
40 & 6.77279e-05 & 0.000135456 & 0.999932 \tabularnewline
41 & 5.76946e-05 & 0.000115389 & 0.999942 \tabularnewline
42 & 4.05859e-05 & 8.11719e-05 & 0.999959 \tabularnewline
43 & 0.0088614 & 0.0177228 & 0.991139 \tabularnewline
44 & 0.0431418 & 0.0862836 & 0.956858 \tabularnewline
45 & 0.0689636 & 0.137927 & 0.931036 \tabularnewline
46 & 0.093828 & 0.187656 & 0.906172 \tabularnewline
47 & 0.11819 & 0.23638 & 0.88181 \tabularnewline
48 & 0.137301 & 0.274601 & 0.862699 \tabularnewline
49 & 0.263295 & 0.526591 & 0.736705 \tabularnewline
50 & 0.373833 & 0.747666 & 0.626167 \tabularnewline
51 & 0.499888 & 0.999777 & 0.500112 \tabularnewline
52 & 0.601541 & 0.796919 & 0.398459 \tabularnewline
53 & 0.697583 & 0.604835 & 0.302417 \tabularnewline
54 & 0.781208 & 0.437584 & 0.218792 \tabularnewline
55 & 0.747482 & 0.505036 & 0.252518 \tabularnewline
56 & 0.710738 & 0.578525 & 0.289262 \tabularnewline
57 & 0.673165 & 0.65367 & 0.326835 \tabularnewline
58 & 0.639871 & 0.720258 & 0.360129 \tabularnewline
59 & 0.603385 & 0.793229 & 0.396615 \tabularnewline
60 & 0.560732 & 0.878535 & 0.439268 \tabularnewline
61 & 0.594506 & 0.810988 & 0.405494 \tabularnewline
62 & 0.620047 & 0.759907 & 0.379953 \tabularnewline
63 & 0.640706 & 0.718588 & 0.359294 \tabularnewline
64 & 0.639313 & 0.721373 & 0.360687 \tabularnewline
65 & 0.631272 & 0.737456 & 0.368728 \tabularnewline
66 & 0.64019 & 0.71962 & 0.35981 \tabularnewline
67 & 0.603396 & 0.793208 & 0.396604 \tabularnewline
68 & 0.564204 & 0.871593 & 0.435796 \tabularnewline
69 & 0.551214 & 0.897571 & 0.448786 \tabularnewline
70 & 0.513006 & 0.973987 & 0.486994 \tabularnewline
71 & 0.472755 & 0.94551 & 0.527245 \tabularnewline
72 & 0.437589 & 0.875177 & 0.562411 \tabularnewline
73 & 0.430379 & 0.860759 & 0.569621 \tabularnewline
74 & 0.401025 & 0.80205 & 0.598975 \tabularnewline
75 & 0.375012 & 0.750024 & 0.624988 \tabularnewline
76 & 0.348427 & 0.696854 & 0.651573 \tabularnewline
77 & 0.315426 & 0.630853 & 0.684574 \tabularnewline
78 & 0.291557 & 0.583114 & 0.708443 \tabularnewline
79 & 0.256424 & 0.512848 & 0.743576 \tabularnewline
80 & 0.228346 & 0.456692 & 0.771654 \tabularnewline
81 & 0.198043 & 0.396086 & 0.801957 \tabularnewline
82 & 0.170413 & 0.340827 & 0.829587 \tabularnewline
83 & 0.144795 & 0.28959 & 0.855205 \tabularnewline
84 & 0.123838 & 0.247677 & 0.876162 \tabularnewline
85 & 0.126377 & 0.252753 & 0.873623 \tabularnewline
86 & 0.107742 & 0.215485 & 0.892258 \tabularnewline
87 & 0.091341 & 0.182682 & 0.908659 \tabularnewline
88 & 0.0859321 & 0.171864 & 0.914068 \tabularnewline
89 & 0.0759844 & 0.151969 & 0.924016 \tabularnewline
90 & 0.0763136 & 0.152627 & 0.923686 \tabularnewline
91 & 0.0711041 & 0.142208 & 0.928896 \tabularnewline
92 & 0.0611722 & 0.122344 & 0.938828 \tabularnewline
93 & 0.0516241 & 0.103248 & 0.948376 \tabularnewline
94 & 0.0478272 & 0.0956544 & 0.952173 \tabularnewline
95 & 0.0426044 & 0.0852088 & 0.957396 \tabularnewline
96 & 0.0391567 & 0.0783134 & 0.960843 \tabularnewline
97 & 0.0407181 & 0.0814362 & 0.959282 \tabularnewline
98 & 0.0324698 & 0.0649396 & 0.96753 \tabularnewline
99 & 0.0262095 & 0.0524191 & 0.97379 \tabularnewline
100 & 0.020535 & 0.0410699 & 0.979465 \tabularnewline
101 & 0.0159766 & 0.0319533 & 0.984023 \tabularnewline
102 & 0.0126956 & 0.0253912 & 0.987304 \tabularnewline
103 & 0.00983344 & 0.0196669 & 0.990167 \tabularnewline
104 & 0.0123168 & 0.0246337 & 0.987683 \tabularnewline
105 & 0.0196925 & 0.039385 & 0.980308 \tabularnewline
106 & 0.0225376 & 0.0450752 & 0.977462 \tabularnewline
107 & 0.0347573 & 0.0695146 & 0.965243 \tabularnewline
108 & 0.0391326 & 0.0782652 & 0.960867 \tabularnewline
109 & 0.060516 & 0.121032 & 0.939484 \tabularnewline
110 & 0.0516093 & 0.103219 & 0.948391 \tabularnewline
111 & 0.0474822 & 0.0949645 & 0.952518 \tabularnewline
112 & 0.0493088 & 0.0986175 & 0.950691 \tabularnewline
113 & 0.0426137 & 0.0852274 & 0.957386 \tabularnewline
114 & 0.0402809 & 0.0805618 & 0.959719 \tabularnewline
115 & 0.0437465 & 0.0874929 & 0.956254 \tabularnewline
116 & 0.0523561 & 0.104712 & 0.947644 \tabularnewline
117 & 0.065599 & 0.131198 & 0.934401 \tabularnewline
118 & 0.0717753 & 0.143551 & 0.928225 \tabularnewline
119 & 0.0832583 & 0.166517 & 0.916742 \tabularnewline
120 & 0.126295 & 0.252589 & 0.873705 \tabularnewline
121 & 0.13588 & 0.271759 & 0.86412 \tabularnewline
122 & 0.211168 & 0.422336 & 0.788832 \tabularnewline
123 & 0.182456 & 0.364913 & 0.817544 \tabularnewline
124 & 0.155358 & 0.310716 & 0.844642 \tabularnewline
125 & 0.131103 & 0.262206 & 0.868897 \tabularnewline
126 & 0.110262 & 0.220524 & 0.889738 \tabularnewline
127 & 0.091896 & 0.183792 & 0.908104 \tabularnewline
128 & 0.075213 & 0.150426 & 0.924787 \tabularnewline
129 & 0.0969007 & 0.193801 & 0.903099 \tabularnewline
130 & 0.105705 & 0.211411 & 0.894295 \tabularnewline
131 & 0.111528 & 0.223056 & 0.888472 \tabularnewline
132 & 0.126784 & 0.253569 & 0.873216 \tabularnewline
133 & 0.133206 & 0.266411 & 0.866794 \tabularnewline
134 & 0.155954 & 0.311908 & 0.844046 \tabularnewline
135 & 0.134123 & 0.268246 & 0.865877 \tabularnewline
136 & 0.111986 & 0.223972 & 0.888014 \tabularnewline
137 & 0.0920064 & 0.184013 & 0.907994 \tabularnewline
138 & 0.0748892 & 0.149778 & 0.925111 \tabularnewline
139 & 0.0603711 & 0.120742 & 0.939629 \tabularnewline
140 & 0.0479742 & 0.0959484 & 0.952026 \tabularnewline
141 & 0.0376854 & 0.0753707 & 0.962315 \tabularnewline
142 & 0.0292889 & 0.0585778 & 0.970711 \tabularnewline
143 & 0.0233512 & 0.0467023 & 0.976649 \tabularnewline
144 & 0.023051 & 0.046102 & 0.976949 \tabularnewline
145 & 0.0313193 & 0.0626387 & 0.968681 \tabularnewline
146 & 0.0540804 & 0.108161 & 0.94592 \tabularnewline
147 & 0.0489824 & 0.0979647 & 0.951018 \tabularnewline
148 & 0.0384605 & 0.0769211 & 0.961539 \tabularnewline
149 & 0.0315002 & 0.0630004 & 0.9685 \tabularnewline
150 & 0.0250131 & 0.0500262 & 0.974987 \tabularnewline
151 & 0.0189067 & 0.0378133 & 0.981093 \tabularnewline
152 & 0.0175872 & 0.0351744 & 0.982413 \tabularnewline
153 & 0.0207638 & 0.0415276 & 0.979236 \tabularnewline
154 & 0.0218889 & 0.0437779 & 0.978111 \tabularnewline
155 & 0.0201305 & 0.0402609 & 0.97987 \tabularnewline
156 & 0.0239198 & 0.0478396 & 0.97608 \tabularnewline
157 & 0.0568266 & 0.113653 & 0.943173 \tabularnewline
158 & 0.0768288 & 0.153658 & 0.923171 \tabularnewline
159 & 0.184518 & 0.369037 & 0.815482 \tabularnewline
160 & 0.172677 & 0.345354 & 0.827323 \tabularnewline
161 & 0.157115 & 0.314231 & 0.842885 \tabularnewline
162 & 0.164091 & 0.328182 & 0.835909 \tabularnewline
163 & 0.132405 & 0.26481 & 0.867595 \tabularnewline
164 & 0.214466 & 0.428932 & 0.785534 \tabularnewline
165 & 0.310943 & 0.621885 & 0.689057 \tabularnewline
166 & 0.309364 & 0.618728 & 0.690636 \tabularnewline
167 & 0.327686 & 0.655373 & 0.672314 \tabularnewline
168 & 0.316532 & 0.633063 & 0.683468 \tabularnewline
169 & 0.558378 & 0.883243 & 0.441622 \tabularnewline
170 & 0.520477 & 0.959046 & 0.479523 \tabularnewline
171 & 0.488471 & 0.976942 & 0.511529 \tabularnewline
172 & 0.481161 & 0.962322 & 0.518839 \tabularnewline
173 & 0.53313 & 0.93374 & 0.46687 \tabularnewline
174 & 0.592621 & 0.814759 & 0.407379 \tabularnewline
175 & 0.712859 & 0.574282 & 0.287141 \tabularnewline
176 & 0.897306 & 0.205388 & 0.102694 \tabularnewline
177 & 0.99999 & 1.90183e-05 & 9.50914e-06 \tabularnewline
178 & 0.999989 & 2.2361e-05 & 1.11805e-05 \tabularnewline
179 & 0.999961 & 7.72862e-05 & 3.86431e-05 \tabularnewline
180 & 0.999906 & 0.000187984 & 9.39922e-05 \tabularnewline
181 & 0.999715 & 0.000569436 & 0.000284718 \tabularnewline
182 & 0.999071 & 0.00185783 & 0.000928914 \tabularnewline
183 & 1 & 0 & 0 \tabularnewline
184 & 1 & 0 & 0 \tabularnewline
185 & 1 & 0 & 0 \tabularnewline
186 & 1 & 0 & 0 \tabularnewline
187 & 1 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231292&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]8[/C][C]4.39888e-48[/C][C]8.79776e-48[/C][C]1[/C][/ROW]
[ROW][C]9[/C][C]5.6114e-65[/C][C]1.12228e-64[/C][C]1[/C][/ROW]
[ROW][C]10[/C][C]8.3199e-81[/C][C]1.66398e-80[/C][C]1[/C][/ROW]
[ROW][C]11[/C][C]1.20902e-94[/C][C]2.41803e-94[/C][C]1[/C][/ROW]
[ROW][C]12[/C][C]2.83547e-107[/C][C]5.67094e-107[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]9.17441e-143[/C][C]1.83488e-142[/C][C]1[/C][/ROW]
[ROW][C]14[/C][C]1.88764e-140[/C][C]3.77528e-140[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]1.12319e-154[/C][C]2.24637e-154[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]4.49195e-200[/C][C]8.98391e-200[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]2.64057e-198[/C][C]5.28115e-198[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]2.80252e-214[/C][C]5.60503e-214[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]9.74994e-244[/C][C]1.94999e-243[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]9.48401e-280[/C][C]1.8968e-279[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]1.76907e-257[/C][C]3.53814e-257[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]3.61254e-277[/C][C]7.22507e-277[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]5.11939e-288[/C][C]1.02388e-287[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]7.30300000047781e-315[/C][C]1.46060000009556e-314[/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]9.51424e-06[/C][C]1.90285e-05[/C][C]0.99999[/C][/ROW]
[ROW][C]32[/C][C]0.000216986[/C][C]0.000433972[/C][C]0.999783[/C][/ROW]
[ROW][C]33[/C][C]0.000504314[/C][C]0.00100863[/C][C]0.999496[/C][/ROW]
[ROW][C]34[/C][C]0.000397879[/C][C]0.000795758[/C][C]0.999602[/C][/ROW]
[ROW][C]35[/C][C]0.000264554[/C][C]0.000529108[/C][C]0.999735[/C][/ROW]
[ROW][C]36[/C][C]0.00022037[/C][C]0.00044074[/C][C]0.99978[/C][/ROW]
[ROW][C]37[/C][C]0.000123193[/C][C]0.000246387[/C][C]0.999877[/C][/ROW]
[ROW][C]38[/C][C]7.94036e-05[/C][C]0.000158807[/C][C]0.999921[/C][/ROW]
[ROW][C]39[/C][C]8.37099e-05[/C][C]0.00016742[/C][C]0.999916[/C][/ROW]
[ROW][C]40[/C][C]6.77279e-05[/C][C]0.000135456[/C][C]0.999932[/C][/ROW]
[ROW][C]41[/C][C]5.76946e-05[/C][C]0.000115389[/C][C]0.999942[/C][/ROW]
[ROW][C]42[/C][C]4.05859e-05[/C][C]8.11719e-05[/C][C]0.999959[/C][/ROW]
[ROW][C]43[/C][C]0.0088614[/C][C]0.0177228[/C][C]0.991139[/C][/ROW]
[ROW][C]44[/C][C]0.0431418[/C][C]0.0862836[/C][C]0.956858[/C][/ROW]
[ROW][C]45[/C][C]0.0689636[/C][C]0.137927[/C][C]0.931036[/C][/ROW]
[ROW][C]46[/C][C]0.093828[/C][C]0.187656[/C][C]0.906172[/C][/ROW]
[ROW][C]47[/C][C]0.11819[/C][C]0.23638[/C][C]0.88181[/C][/ROW]
[ROW][C]48[/C][C]0.137301[/C][C]0.274601[/C][C]0.862699[/C][/ROW]
[ROW][C]49[/C][C]0.263295[/C][C]0.526591[/C][C]0.736705[/C][/ROW]
[ROW][C]50[/C][C]0.373833[/C][C]0.747666[/C][C]0.626167[/C][/ROW]
[ROW][C]51[/C][C]0.499888[/C][C]0.999777[/C][C]0.500112[/C][/ROW]
[ROW][C]52[/C][C]0.601541[/C][C]0.796919[/C][C]0.398459[/C][/ROW]
[ROW][C]53[/C][C]0.697583[/C][C]0.604835[/C][C]0.302417[/C][/ROW]
[ROW][C]54[/C][C]0.781208[/C][C]0.437584[/C][C]0.218792[/C][/ROW]
[ROW][C]55[/C][C]0.747482[/C][C]0.505036[/C][C]0.252518[/C][/ROW]
[ROW][C]56[/C][C]0.710738[/C][C]0.578525[/C][C]0.289262[/C][/ROW]
[ROW][C]57[/C][C]0.673165[/C][C]0.65367[/C][C]0.326835[/C][/ROW]
[ROW][C]58[/C][C]0.639871[/C][C]0.720258[/C][C]0.360129[/C][/ROW]
[ROW][C]59[/C][C]0.603385[/C][C]0.793229[/C][C]0.396615[/C][/ROW]
[ROW][C]60[/C][C]0.560732[/C][C]0.878535[/C][C]0.439268[/C][/ROW]
[ROW][C]61[/C][C]0.594506[/C][C]0.810988[/C][C]0.405494[/C][/ROW]
[ROW][C]62[/C][C]0.620047[/C][C]0.759907[/C][C]0.379953[/C][/ROW]
[ROW][C]63[/C][C]0.640706[/C][C]0.718588[/C][C]0.359294[/C][/ROW]
[ROW][C]64[/C][C]0.639313[/C][C]0.721373[/C][C]0.360687[/C][/ROW]
[ROW][C]65[/C][C]0.631272[/C][C]0.737456[/C][C]0.368728[/C][/ROW]
[ROW][C]66[/C][C]0.64019[/C][C]0.71962[/C][C]0.35981[/C][/ROW]
[ROW][C]67[/C][C]0.603396[/C][C]0.793208[/C][C]0.396604[/C][/ROW]
[ROW][C]68[/C][C]0.564204[/C][C]0.871593[/C][C]0.435796[/C][/ROW]
[ROW][C]69[/C][C]0.551214[/C][C]0.897571[/C][C]0.448786[/C][/ROW]
[ROW][C]70[/C][C]0.513006[/C][C]0.973987[/C][C]0.486994[/C][/ROW]
[ROW][C]71[/C][C]0.472755[/C][C]0.94551[/C][C]0.527245[/C][/ROW]
[ROW][C]72[/C][C]0.437589[/C][C]0.875177[/C][C]0.562411[/C][/ROW]
[ROW][C]73[/C][C]0.430379[/C][C]0.860759[/C][C]0.569621[/C][/ROW]
[ROW][C]74[/C][C]0.401025[/C][C]0.80205[/C][C]0.598975[/C][/ROW]
[ROW][C]75[/C][C]0.375012[/C][C]0.750024[/C][C]0.624988[/C][/ROW]
[ROW][C]76[/C][C]0.348427[/C][C]0.696854[/C][C]0.651573[/C][/ROW]
[ROW][C]77[/C][C]0.315426[/C][C]0.630853[/C][C]0.684574[/C][/ROW]
[ROW][C]78[/C][C]0.291557[/C][C]0.583114[/C][C]0.708443[/C][/ROW]
[ROW][C]79[/C][C]0.256424[/C][C]0.512848[/C][C]0.743576[/C][/ROW]
[ROW][C]80[/C][C]0.228346[/C][C]0.456692[/C][C]0.771654[/C][/ROW]
[ROW][C]81[/C][C]0.198043[/C][C]0.396086[/C][C]0.801957[/C][/ROW]
[ROW][C]82[/C][C]0.170413[/C][C]0.340827[/C][C]0.829587[/C][/ROW]
[ROW][C]83[/C][C]0.144795[/C][C]0.28959[/C][C]0.855205[/C][/ROW]
[ROW][C]84[/C][C]0.123838[/C][C]0.247677[/C][C]0.876162[/C][/ROW]
[ROW][C]85[/C][C]0.126377[/C][C]0.252753[/C][C]0.873623[/C][/ROW]
[ROW][C]86[/C][C]0.107742[/C][C]0.215485[/C][C]0.892258[/C][/ROW]
[ROW][C]87[/C][C]0.091341[/C][C]0.182682[/C][C]0.908659[/C][/ROW]
[ROW][C]88[/C][C]0.0859321[/C][C]0.171864[/C][C]0.914068[/C][/ROW]
[ROW][C]89[/C][C]0.0759844[/C][C]0.151969[/C][C]0.924016[/C][/ROW]
[ROW][C]90[/C][C]0.0763136[/C][C]0.152627[/C][C]0.923686[/C][/ROW]
[ROW][C]91[/C][C]0.0711041[/C][C]0.142208[/C][C]0.928896[/C][/ROW]
[ROW][C]92[/C][C]0.0611722[/C][C]0.122344[/C][C]0.938828[/C][/ROW]
[ROW][C]93[/C][C]0.0516241[/C][C]0.103248[/C][C]0.948376[/C][/ROW]
[ROW][C]94[/C][C]0.0478272[/C][C]0.0956544[/C][C]0.952173[/C][/ROW]
[ROW][C]95[/C][C]0.0426044[/C][C]0.0852088[/C][C]0.957396[/C][/ROW]
[ROW][C]96[/C][C]0.0391567[/C][C]0.0783134[/C][C]0.960843[/C][/ROW]
[ROW][C]97[/C][C]0.0407181[/C][C]0.0814362[/C][C]0.959282[/C][/ROW]
[ROW][C]98[/C][C]0.0324698[/C][C]0.0649396[/C][C]0.96753[/C][/ROW]
[ROW][C]99[/C][C]0.0262095[/C][C]0.0524191[/C][C]0.97379[/C][/ROW]
[ROW][C]100[/C][C]0.020535[/C][C]0.0410699[/C][C]0.979465[/C][/ROW]
[ROW][C]101[/C][C]0.0159766[/C][C]0.0319533[/C][C]0.984023[/C][/ROW]
[ROW][C]102[/C][C]0.0126956[/C][C]0.0253912[/C][C]0.987304[/C][/ROW]
[ROW][C]103[/C][C]0.00983344[/C][C]0.0196669[/C][C]0.990167[/C][/ROW]
[ROW][C]104[/C][C]0.0123168[/C][C]0.0246337[/C][C]0.987683[/C][/ROW]
[ROW][C]105[/C][C]0.0196925[/C][C]0.039385[/C][C]0.980308[/C][/ROW]
[ROW][C]106[/C][C]0.0225376[/C][C]0.0450752[/C][C]0.977462[/C][/ROW]
[ROW][C]107[/C][C]0.0347573[/C][C]0.0695146[/C][C]0.965243[/C][/ROW]
[ROW][C]108[/C][C]0.0391326[/C][C]0.0782652[/C][C]0.960867[/C][/ROW]
[ROW][C]109[/C][C]0.060516[/C][C]0.121032[/C][C]0.939484[/C][/ROW]
[ROW][C]110[/C][C]0.0516093[/C][C]0.103219[/C][C]0.948391[/C][/ROW]
[ROW][C]111[/C][C]0.0474822[/C][C]0.0949645[/C][C]0.952518[/C][/ROW]
[ROW][C]112[/C][C]0.0493088[/C][C]0.0986175[/C][C]0.950691[/C][/ROW]
[ROW][C]113[/C][C]0.0426137[/C][C]0.0852274[/C][C]0.957386[/C][/ROW]
[ROW][C]114[/C][C]0.0402809[/C][C]0.0805618[/C][C]0.959719[/C][/ROW]
[ROW][C]115[/C][C]0.0437465[/C][C]0.0874929[/C][C]0.956254[/C][/ROW]
[ROW][C]116[/C][C]0.0523561[/C][C]0.104712[/C][C]0.947644[/C][/ROW]
[ROW][C]117[/C][C]0.065599[/C][C]0.131198[/C][C]0.934401[/C][/ROW]
[ROW][C]118[/C][C]0.0717753[/C][C]0.143551[/C][C]0.928225[/C][/ROW]
[ROW][C]119[/C][C]0.0832583[/C][C]0.166517[/C][C]0.916742[/C][/ROW]
[ROW][C]120[/C][C]0.126295[/C][C]0.252589[/C][C]0.873705[/C][/ROW]
[ROW][C]121[/C][C]0.13588[/C][C]0.271759[/C][C]0.86412[/C][/ROW]
[ROW][C]122[/C][C]0.211168[/C][C]0.422336[/C][C]0.788832[/C][/ROW]
[ROW][C]123[/C][C]0.182456[/C][C]0.364913[/C][C]0.817544[/C][/ROW]
[ROW][C]124[/C][C]0.155358[/C][C]0.310716[/C][C]0.844642[/C][/ROW]
[ROW][C]125[/C][C]0.131103[/C][C]0.262206[/C][C]0.868897[/C][/ROW]
[ROW][C]126[/C][C]0.110262[/C][C]0.220524[/C][C]0.889738[/C][/ROW]
[ROW][C]127[/C][C]0.091896[/C][C]0.183792[/C][C]0.908104[/C][/ROW]
[ROW][C]128[/C][C]0.075213[/C][C]0.150426[/C][C]0.924787[/C][/ROW]
[ROW][C]129[/C][C]0.0969007[/C][C]0.193801[/C][C]0.903099[/C][/ROW]
[ROW][C]130[/C][C]0.105705[/C][C]0.211411[/C][C]0.894295[/C][/ROW]
[ROW][C]131[/C][C]0.111528[/C][C]0.223056[/C][C]0.888472[/C][/ROW]
[ROW][C]132[/C][C]0.126784[/C][C]0.253569[/C][C]0.873216[/C][/ROW]
[ROW][C]133[/C][C]0.133206[/C][C]0.266411[/C][C]0.866794[/C][/ROW]
[ROW][C]134[/C][C]0.155954[/C][C]0.311908[/C][C]0.844046[/C][/ROW]
[ROW][C]135[/C][C]0.134123[/C][C]0.268246[/C][C]0.865877[/C][/ROW]
[ROW][C]136[/C][C]0.111986[/C][C]0.223972[/C][C]0.888014[/C][/ROW]
[ROW][C]137[/C][C]0.0920064[/C][C]0.184013[/C][C]0.907994[/C][/ROW]
[ROW][C]138[/C][C]0.0748892[/C][C]0.149778[/C][C]0.925111[/C][/ROW]
[ROW][C]139[/C][C]0.0603711[/C][C]0.120742[/C][C]0.939629[/C][/ROW]
[ROW][C]140[/C][C]0.0479742[/C][C]0.0959484[/C][C]0.952026[/C][/ROW]
[ROW][C]141[/C][C]0.0376854[/C][C]0.0753707[/C][C]0.962315[/C][/ROW]
[ROW][C]142[/C][C]0.0292889[/C][C]0.0585778[/C][C]0.970711[/C][/ROW]
[ROW][C]143[/C][C]0.0233512[/C][C]0.0467023[/C][C]0.976649[/C][/ROW]
[ROW][C]144[/C][C]0.023051[/C][C]0.046102[/C][C]0.976949[/C][/ROW]
[ROW][C]145[/C][C]0.0313193[/C][C]0.0626387[/C][C]0.968681[/C][/ROW]
[ROW][C]146[/C][C]0.0540804[/C][C]0.108161[/C][C]0.94592[/C][/ROW]
[ROW][C]147[/C][C]0.0489824[/C][C]0.0979647[/C][C]0.951018[/C][/ROW]
[ROW][C]148[/C][C]0.0384605[/C][C]0.0769211[/C][C]0.961539[/C][/ROW]
[ROW][C]149[/C][C]0.0315002[/C][C]0.0630004[/C][C]0.9685[/C][/ROW]
[ROW][C]150[/C][C]0.0250131[/C][C]0.0500262[/C][C]0.974987[/C][/ROW]
[ROW][C]151[/C][C]0.0189067[/C][C]0.0378133[/C][C]0.981093[/C][/ROW]
[ROW][C]152[/C][C]0.0175872[/C][C]0.0351744[/C][C]0.982413[/C][/ROW]
[ROW][C]153[/C][C]0.0207638[/C][C]0.0415276[/C][C]0.979236[/C][/ROW]
[ROW][C]154[/C][C]0.0218889[/C][C]0.0437779[/C][C]0.978111[/C][/ROW]
[ROW][C]155[/C][C]0.0201305[/C][C]0.0402609[/C][C]0.97987[/C][/ROW]
[ROW][C]156[/C][C]0.0239198[/C][C]0.0478396[/C][C]0.97608[/C][/ROW]
[ROW][C]157[/C][C]0.0568266[/C][C]0.113653[/C][C]0.943173[/C][/ROW]
[ROW][C]158[/C][C]0.0768288[/C][C]0.153658[/C][C]0.923171[/C][/ROW]
[ROW][C]159[/C][C]0.184518[/C][C]0.369037[/C][C]0.815482[/C][/ROW]
[ROW][C]160[/C][C]0.172677[/C][C]0.345354[/C][C]0.827323[/C][/ROW]
[ROW][C]161[/C][C]0.157115[/C][C]0.314231[/C][C]0.842885[/C][/ROW]
[ROW][C]162[/C][C]0.164091[/C][C]0.328182[/C][C]0.835909[/C][/ROW]
[ROW][C]163[/C][C]0.132405[/C][C]0.26481[/C][C]0.867595[/C][/ROW]
[ROW][C]164[/C][C]0.214466[/C][C]0.428932[/C][C]0.785534[/C][/ROW]
[ROW][C]165[/C][C]0.310943[/C][C]0.621885[/C][C]0.689057[/C][/ROW]
[ROW][C]166[/C][C]0.309364[/C][C]0.618728[/C][C]0.690636[/C][/ROW]
[ROW][C]167[/C][C]0.327686[/C][C]0.655373[/C][C]0.672314[/C][/ROW]
[ROW][C]168[/C][C]0.316532[/C][C]0.633063[/C][C]0.683468[/C][/ROW]
[ROW][C]169[/C][C]0.558378[/C][C]0.883243[/C][C]0.441622[/C][/ROW]
[ROW][C]170[/C][C]0.520477[/C][C]0.959046[/C][C]0.479523[/C][/ROW]
[ROW][C]171[/C][C]0.488471[/C][C]0.976942[/C][C]0.511529[/C][/ROW]
[ROW][C]172[/C][C]0.481161[/C][C]0.962322[/C][C]0.518839[/C][/ROW]
[ROW][C]173[/C][C]0.53313[/C][C]0.93374[/C][C]0.46687[/C][/ROW]
[ROW][C]174[/C][C]0.592621[/C][C]0.814759[/C][C]0.407379[/C][/ROW]
[ROW][C]175[/C][C]0.712859[/C][C]0.574282[/C][C]0.287141[/C][/ROW]
[ROW][C]176[/C][C]0.897306[/C][C]0.205388[/C][C]0.102694[/C][/ROW]
[ROW][C]177[/C][C]0.99999[/C][C]1.90183e-05[/C][C]9.50914e-06[/C][/ROW]
[ROW][C]178[/C][C]0.999989[/C][C]2.2361e-05[/C][C]1.11805e-05[/C][/ROW]
[ROW][C]179[/C][C]0.999961[/C][C]7.72862e-05[/C][C]3.86431e-05[/C][/ROW]
[ROW][C]180[/C][C]0.999906[/C][C]0.000187984[/C][C]9.39922e-05[/C][/ROW]
[ROW][C]181[/C][C]0.999715[/C][C]0.000569436[/C][C]0.000284718[/C][/ROW]
[ROW][C]182[/C][C]0.999071[/C][C]0.00185783[/C][C]0.000928914[/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]
[ROW][C]187[/C][C]1[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231292&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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
84.39888e-488.79776e-481
95.6114e-651.12228e-641
108.3199e-811.66398e-801
111.20902e-942.41803e-941
122.83547e-1075.67094e-1071
139.17441e-1431.83488e-1421
141.88764e-1403.77528e-1401
151.12319e-1542.24637e-1541
16001
174.49195e-2008.98391e-2001
182.64057e-1985.28115e-1981
192.80252e-2145.60503e-2141
209.74994e-2441.94999e-2431
219.48401e-2801.8968e-2791
221.76907e-2573.53814e-2571
233.61254e-2777.22507e-2771
245.11939e-2881.02388e-2871
257.30300000047781e-3151.46060000009556e-3141
26001
27001
28001
29001
30001
319.51424e-061.90285e-050.99999
320.0002169860.0004339720.999783
330.0005043140.001008630.999496
340.0003978790.0007957580.999602
350.0002645540.0005291080.999735
360.000220370.000440740.99978
370.0001231930.0002463870.999877
387.94036e-050.0001588070.999921
398.37099e-050.000167420.999916
406.77279e-050.0001354560.999932
415.76946e-050.0001153890.999942
424.05859e-058.11719e-050.999959
430.00886140.01772280.991139
440.04314180.08628360.956858
450.06896360.1379270.931036
460.0938280.1876560.906172
470.118190.236380.88181
480.1373010.2746010.862699
490.2632950.5265910.736705
500.3738330.7476660.626167
510.4998880.9997770.500112
520.6015410.7969190.398459
530.6975830.6048350.302417
540.7812080.4375840.218792
550.7474820.5050360.252518
560.7107380.5785250.289262
570.6731650.653670.326835
580.6398710.7202580.360129
590.6033850.7932290.396615
600.5607320.8785350.439268
610.5945060.8109880.405494
620.6200470.7599070.379953
630.6407060.7185880.359294
640.6393130.7213730.360687
650.6312720.7374560.368728
660.640190.719620.35981
670.6033960.7932080.396604
680.5642040.8715930.435796
690.5512140.8975710.448786
700.5130060.9739870.486994
710.4727550.945510.527245
720.4375890.8751770.562411
730.4303790.8607590.569621
740.4010250.802050.598975
750.3750120.7500240.624988
760.3484270.6968540.651573
770.3154260.6308530.684574
780.2915570.5831140.708443
790.2564240.5128480.743576
800.2283460.4566920.771654
810.1980430.3960860.801957
820.1704130.3408270.829587
830.1447950.289590.855205
840.1238380.2476770.876162
850.1263770.2527530.873623
860.1077420.2154850.892258
870.0913410.1826820.908659
880.08593210.1718640.914068
890.07598440.1519690.924016
900.07631360.1526270.923686
910.07110410.1422080.928896
920.06117220.1223440.938828
930.05162410.1032480.948376
940.04782720.09565440.952173
950.04260440.08520880.957396
960.03915670.07831340.960843
970.04071810.08143620.959282
980.03246980.06493960.96753
990.02620950.05241910.97379
1000.0205350.04106990.979465
1010.01597660.03195330.984023
1020.01269560.02539120.987304
1030.009833440.01966690.990167
1040.01231680.02463370.987683
1050.01969250.0393850.980308
1060.02253760.04507520.977462
1070.03475730.06951460.965243
1080.03913260.07826520.960867
1090.0605160.1210320.939484
1100.05160930.1032190.948391
1110.04748220.09496450.952518
1120.04930880.09861750.950691
1130.04261370.08522740.957386
1140.04028090.08056180.959719
1150.04374650.08749290.956254
1160.05235610.1047120.947644
1170.0655990.1311980.934401
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1190.08325830.1665170.916742
1200.1262950.2525890.873705
1210.135880.2717590.86412
1220.2111680.4223360.788832
1230.1824560.3649130.817544
1240.1553580.3107160.844642
1250.1311030.2622060.868897
1260.1102620.2205240.889738
1270.0918960.1837920.908104
1280.0752130.1504260.924787
1290.09690070.1938010.903099
1300.1057050.2114110.894295
1310.1115280.2230560.888472
1320.1267840.2535690.873216
1330.1332060.2664110.866794
1340.1559540.3119080.844046
1350.1341230.2682460.865877
1360.1119860.2239720.888014
1370.09200640.1840130.907994
1380.07488920.1497780.925111
1390.06037110.1207420.939629
1400.04797420.09594840.952026
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1420.02928890.05857780.970711
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1500.02501310.05002620.974987
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1760.8973060.2053880.102694
1770.999991.90183e-059.50914e-06
1780.9999892.2361e-051.11805e-05
1790.9999617.72862e-053.86431e-05
1800.9999060.0001879849.39922e-05
1810.9997150.0005694360.000284718
1820.9990710.001857830.000928914
183100
184100
185100
186100
187100







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level460.255556NOK
5% type I error level620.344444NOK
10% type I error level840.466667NOK

\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 & 46 & 0.255556 & NOK \tabularnewline
5% type I error level & 62 & 0.344444 & NOK \tabularnewline
10% type I error level & 84 & 0.466667 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231292&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]46[/C][C]0.255556[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]62[/C][C]0.344444[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]84[/C][C]0.466667[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231292&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231292&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 level460.255556NOK
5% type I error level620.344444NOK
10% type I error level840.466667NOK



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')
}