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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 27 Nov 2009 01:52:28 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/27/t12593120989m5sw2are5sa1pa.htm/, Retrieved Sun, 28 Apr 2024 21:39:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60483, Retrieved Sun, 28 Apr 2024 21:39:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact208

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [workshop 8 bereke...] [2009-11-27 08:52:28] [78d370e6d5f4594e9982a5085e7604c6] [Current]
-    D            [(Partial) Autocorrelation Function] [workshop 8 ACF] [2009-11-27 13:55:06] [af8eb90b4bf1bcfcc4325c143dbee260]
-   P             [(Partial) Autocorrelation Function] [paper d=D=0] [2009-12-04 14:37:18] [eaf42bcf5162b5692bb3c7f9d4636222]
-    D              [(Partial) Autocorrelation Function] [paper d=D=0 ] [2009-12-13 09:08:29] [eaf42bcf5162b5692bb3c7f9d4636222]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4716.99
4926.65
4920.10
5170.09
5246.24
5283.61
4979.05
4825.20
4695.12
4711.54
4727.22
4384.96
4378.75
4472.93
4564.07
4310.54
4171.38
4049.38
3591.37
3720.46
4107.23
4101.71
4162.34
4136.22
4125.88
4031.48
3761.36
3408.56
3228.47
3090.45
2741.14
2980.44
3104.33
3181.57
2863.86
2898.01
3112.33
3254.33
3513.47
3587.61
3727.45
3793.34
3817.58
3845.13
3931.86
4197.52
4307.13
4229.43
4362.28
4217.34
4361.28
4327.74
4417.65
4557.68
4650.35
4967.18
5123.42
5290.85
5535.66
5514.06
5493.88
5694.83
5850.41
6116.64
6175.00
6513.58
6383.78
6673.66
6936.61
7300.68
7392.93
7497.31
7584.71
7160.79
7196.19
7245.63
7347.51
7425.75
7778.51
7822.33
8181.22
8371.47
8347.71
8672.11
8802.79
9138.46
9123.29
9023.21
8850.41
8864.58
9163.74
8516.66
8553.44
7555.20
7851.22
7442.00
7992.53
8264.04
7517.39
7200.40
7193.69
6193.58
5104.21
4800.46
4461.61
4398.59
4243.63
4293.82

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60483&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60483&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60483&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.98530910.23960
20.96578810.03680
30.9398099.76680
40.9111379.46880
50.8800979.14620
60.849118.82420
70.8200858.52260
80.7904918.2150
90.7599677.89780
100.7265797.55080
110.6939047.21130
120.6554226.81130
130.6140816.38170
140.5729685.95450
150.5306075.51420
160.4908435.1011e-06
170.449334.66964e-06
180.4100394.26132.2e-05
190.3688893.83360.000106
200.3277823.40640.000463
210.2877742.99060.001724
220.2503222.60140.005293
230.2134722.21850.014308
240.1773411.8430.034037
250.1432791.4890.069701
260.1076441.11870.132883
270.0732220.76090.224174
280.0374750.38940.348856
290.0005890.00610.497562
30-0.037021-0.38470.350597
31-0.07423-0.77140.22107
32-0.110059-1.14380.127624
33-0.144823-1.5050.067616
34-0.177314-1.84270.034057
35-0.207853-2.16010.016489
36-0.234481-2.43680.008226

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.985309 & 10.2396 & 0 \tabularnewline
2 & 0.965788 & 10.0368 & 0 \tabularnewline
3 & 0.939809 & 9.7668 & 0 \tabularnewline
4 & 0.911137 & 9.4688 & 0 \tabularnewline
5 & 0.880097 & 9.1462 & 0 \tabularnewline
6 & 0.84911 & 8.8242 & 0 \tabularnewline
7 & 0.820085 & 8.5226 & 0 \tabularnewline
8 & 0.790491 & 8.215 & 0 \tabularnewline
9 & 0.759967 & 7.8978 & 0 \tabularnewline
10 & 0.726579 & 7.5508 & 0 \tabularnewline
11 & 0.693904 & 7.2113 & 0 \tabularnewline
12 & 0.655422 & 6.8113 & 0 \tabularnewline
13 & 0.614081 & 6.3817 & 0 \tabularnewline
14 & 0.572968 & 5.9545 & 0 \tabularnewline
15 & 0.530607 & 5.5142 & 0 \tabularnewline
16 & 0.490843 & 5.101 & 1e-06 \tabularnewline
17 & 0.44933 & 4.6696 & 4e-06 \tabularnewline
18 & 0.410039 & 4.2613 & 2.2e-05 \tabularnewline
19 & 0.368889 & 3.8336 & 0.000106 \tabularnewline
20 & 0.327782 & 3.4064 & 0.000463 \tabularnewline
21 & 0.287774 & 2.9906 & 0.001724 \tabularnewline
22 & 0.250322 & 2.6014 & 0.005293 \tabularnewline
23 & 0.213472 & 2.2185 & 0.014308 \tabularnewline
24 & 0.177341 & 1.843 & 0.034037 \tabularnewline
25 & 0.143279 & 1.489 & 0.069701 \tabularnewline
26 & 0.107644 & 1.1187 & 0.132883 \tabularnewline
27 & 0.073222 & 0.7609 & 0.224174 \tabularnewline
28 & 0.037475 & 0.3894 & 0.348856 \tabularnewline
29 & 0.000589 & 0.0061 & 0.497562 \tabularnewline
30 & -0.037021 & -0.3847 & 0.350597 \tabularnewline
31 & -0.07423 & -0.7714 & 0.22107 \tabularnewline
32 & -0.110059 & -1.1438 & 0.127624 \tabularnewline
33 & -0.144823 & -1.505 & 0.067616 \tabularnewline
34 & -0.177314 & -1.8427 & 0.034057 \tabularnewline
35 & -0.207853 & -2.1601 & 0.016489 \tabularnewline
36 & -0.234481 & -2.4368 & 0.008226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60483&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.985309[/C][C]10.2396[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.965788[/C][C]10.0368[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.939809[/C][C]9.7668[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.911137[/C][C]9.4688[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.880097[/C][C]9.1462[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.84911[/C][C]8.8242[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.820085[/C][C]8.5226[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.790491[/C][C]8.215[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.759967[/C][C]7.8978[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.726579[/C][C]7.5508[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.693904[/C][C]7.2113[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.655422[/C][C]6.8113[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.614081[/C][C]6.3817[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.572968[/C][C]5.9545[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.530607[/C][C]5.5142[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.490843[/C][C]5.101[/C][C]1e-06[/C][/ROW]
[ROW][C]17[/C][C]0.44933[/C][C]4.6696[/C][C]4e-06[/C][/ROW]
[ROW][C]18[/C][C]0.410039[/C][C]4.2613[/C][C]2.2e-05[/C][/ROW]
[ROW][C]19[/C][C]0.368889[/C][C]3.8336[/C][C]0.000106[/C][/ROW]
[ROW][C]20[/C][C]0.327782[/C][C]3.4064[/C][C]0.000463[/C][/ROW]
[ROW][C]21[/C][C]0.287774[/C][C]2.9906[/C][C]0.001724[/C][/ROW]
[ROW][C]22[/C][C]0.250322[/C][C]2.6014[/C][C]0.005293[/C][/ROW]
[ROW][C]23[/C][C]0.213472[/C][C]2.2185[/C][C]0.014308[/C][/ROW]
[ROW][C]24[/C][C]0.177341[/C][C]1.843[/C][C]0.034037[/C][/ROW]
[ROW][C]25[/C][C]0.143279[/C][C]1.489[/C][C]0.069701[/C][/ROW]
[ROW][C]26[/C][C]0.107644[/C][C]1.1187[/C][C]0.132883[/C][/ROW]
[ROW][C]27[/C][C]0.073222[/C][C]0.7609[/C][C]0.224174[/C][/ROW]
[ROW][C]28[/C][C]0.037475[/C][C]0.3894[/C][C]0.348856[/C][/ROW]
[ROW][C]29[/C][C]0.000589[/C][C]0.0061[/C][C]0.497562[/C][/ROW]
[ROW][C]30[/C][C]-0.037021[/C][C]-0.3847[/C][C]0.350597[/C][/ROW]
[ROW][C]31[/C][C]-0.07423[/C][C]-0.7714[/C][C]0.22107[/C][/ROW]
[ROW][C]32[/C][C]-0.110059[/C][C]-1.1438[/C][C]0.127624[/C][/ROW]
[ROW][C]33[/C][C]-0.144823[/C][C]-1.505[/C][C]0.067616[/C][/ROW]
[ROW][C]34[/C][C]-0.177314[/C][C]-1.8427[/C][C]0.034057[/C][/ROW]
[ROW][C]35[/C][C]-0.207853[/C][C]-2.1601[/C][C]0.016489[/C][/ROW]
[ROW][C]36[/C][C]-0.234481[/C][C]-2.4368[/C][C]0.008226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60483&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60483&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.98530910.23960
20.96578810.03680
30.9398099.76680
40.9111379.46880
50.8800979.14620
60.849118.82420
70.8200858.52260
80.7904918.2150
90.7599677.89780
100.7265797.55080
110.6939047.21130
120.6554226.81130
130.6140816.38170
140.5729685.95450
150.5306075.51420
160.4908435.1011e-06
170.449334.66964e-06
180.4100394.26132.2e-05
190.3688893.83360.000106
200.3277823.40640.000463
210.2877742.99060.001724
220.2503222.60140.005293
230.2134722.21850.014308
240.1773411.8430.034037
250.1432791.4890.069701
260.1076441.11870.132883
270.0732220.76090.224174
280.0374750.38940.348856
290.0005890.00610.497562
30-0.037021-0.38470.350597
31-0.07423-0.77140.22107
32-0.110059-1.14380.127624
33-0.144823-1.5050.067616
34-0.177314-1.84270.034057
35-0.207853-2.16010.016489
36-0.234481-2.43680.008226






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.98530910.23960
2-0.17296-1.79750.037529
3-0.210631-2.18890.015377
4-0.048562-0.50470.307409
5-0.040217-0.41790.338409
60.0247190.25690.398877
70.0752420.78190.217982
8-0.060717-0.6310.26469
9-0.077918-0.80980.209932
10-0.11544-1.19970.116443
110.0435530.45260.325866
12-0.196007-2.0370.02205
13-0.081421-0.84610.199671
140.0790610.82160.20655
15-0.054165-0.56290.287335
160.0770220.80040.212608
17-0.103338-1.07390.142627
18-0.004543-0.04720.481217
19-0.10603-1.10190.136479
20-0.025839-0.26850.394403
210.088070.91530.181049
220.0502290.5220.301371
23-0.035213-0.36590.357561
24-0.00795-0.08260.467155
25-0.0268-0.27850.390575
26-0.105293-1.09420.138142
27-0.018486-0.19210.424008
28-0.03106-0.32280.373739
29-0.091883-0.95490.170888
30-0.039979-0.41550.339308
310.0441280.45860.323724
32-0.033398-0.34710.364604
33-0.051032-0.53030.298483
34-0.011435-0.11880.452812
350.0181950.18910.425189
360.0461330.47940.316302

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.985309 & 10.2396 & 0 \tabularnewline
2 & -0.17296 & -1.7975 & 0.037529 \tabularnewline
3 & -0.210631 & -2.1889 & 0.015377 \tabularnewline
4 & -0.048562 & -0.5047 & 0.307409 \tabularnewline
5 & -0.040217 & -0.4179 & 0.338409 \tabularnewline
6 & 0.024719 & 0.2569 & 0.398877 \tabularnewline
7 & 0.075242 & 0.7819 & 0.217982 \tabularnewline
8 & -0.060717 & -0.631 & 0.26469 \tabularnewline
9 & -0.077918 & -0.8098 & 0.209932 \tabularnewline
10 & -0.11544 & -1.1997 & 0.116443 \tabularnewline
11 & 0.043553 & 0.4526 & 0.325866 \tabularnewline
12 & -0.196007 & -2.037 & 0.02205 \tabularnewline
13 & -0.081421 & -0.8461 & 0.199671 \tabularnewline
14 & 0.079061 & 0.8216 & 0.20655 \tabularnewline
15 & -0.054165 & -0.5629 & 0.287335 \tabularnewline
16 & 0.077022 & 0.8004 & 0.212608 \tabularnewline
17 & -0.103338 & -1.0739 & 0.142627 \tabularnewline
18 & -0.004543 & -0.0472 & 0.481217 \tabularnewline
19 & -0.10603 & -1.1019 & 0.136479 \tabularnewline
20 & -0.025839 & -0.2685 & 0.394403 \tabularnewline
21 & 0.08807 & 0.9153 & 0.181049 \tabularnewline
22 & 0.050229 & 0.522 & 0.301371 \tabularnewline
23 & -0.035213 & -0.3659 & 0.357561 \tabularnewline
24 & -0.00795 & -0.0826 & 0.467155 \tabularnewline
25 & -0.0268 & -0.2785 & 0.390575 \tabularnewline
26 & -0.105293 & -1.0942 & 0.138142 \tabularnewline
27 & -0.018486 & -0.1921 & 0.424008 \tabularnewline
28 & -0.03106 & -0.3228 & 0.373739 \tabularnewline
29 & -0.091883 & -0.9549 & 0.170888 \tabularnewline
30 & -0.039979 & -0.4155 & 0.339308 \tabularnewline
31 & 0.044128 & 0.4586 & 0.323724 \tabularnewline
32 & -0.033398 & -0.3471 & 0.364604 \tabularnewline
33 & -0.051032 & -0.5303 & 0.298483 \tabularnewline
34 & -0.011435 & -0.1188 & 0.452812 \tabularnewline
35 & 0.018195 & 0.1891 & 0.425189 \tabularnewline
36 & 0.046133 & 0.4794 & 0.316302 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60483&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.985309[/C][C]10.2396[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.17296[/C][C]-1.7975[/C][C]0.037529[/C][/ROW]
[ROW][C]3[/C][C]-0.210631[/C][C]-2.1889[/C][C]0.015377[/C][/ROW]
[ROW][C]4[/C][C]-0.048562[/C][C]-0.5047[/C][C]0.307409[/C][/ROW]
[ROW][C]5[/C][C]-0.040217[/C][C]-0.4179[/C][C]0.338409[/C][/ROW]
[ROW][C]6[/C][C]0.024719[/C][C]0.2569[/C][C]0.398877[/C][/ROW]
[ROW][C]7[/C][C]0.075242[/C][C]0.7819[/C][C]0.217982[/C][/ROW]
[ROW][C]8[/C][C]-0.060717[/C][C]-0.631[/C][C]0.26469[/C][/ROW]
[ROW][C]9[/C][C]-0.077918[/C][C]-0.8098[/C][C]0.209932[/C][/ROW]
[ROW][C]10[/C][C]-0.11544[/C][C]-1.1997[/C][C]0.116443[/C][/ROW]
[ROW][C]11[/C][C]0.043553[/C][C]0.4526[/C][C]0.325866[/C][/ROW]
[ROW][C]12[/C][C]-0.196007[/C][C]-2.037[/C][C]0.02205[/C][/ROW]
[ROW][C]13[/C][C]-0.081421[/C][C]-0.8461[/C][C]0.199671[/C][/ROW]
[ROW][C]14[/C][C]0.079061[/C][C]0.8216[/C][C]0.20655[/C][/ROW]
[ROW][C]15[/C][C]-0.054165[/C][C]-0.5629[/C][C]0.287335[/C][/ROW]
[ROW][C]16[/C][C]0.077022[/C][C]0.8004[/C][C]0.212608[/C][/ROW]
[ROW][C]17[/C][C]-0.103338[/C][C]-1.0739[/C][C]0.142627[/C][/ROW]
[ROW][C]18[/C][C]-0.004543[/C][C]-0.0472[/C][C]0.481217[/C][/ROW]
[ROW][C]19[/C][C]-0.10603[/C][C]-1.1019[/C][C]0.136479[/C][/ROW]
[ROW][C]20[/C][C]-0.025839[/C][C]-0.2685[/C][C]0.394403[/C][/ROW]
[ROW][C]21[/C][C]0.08807[/C][C]0.9153[/C][C]0.181049[/C][/ROW]
[ROW][C]22[/C][C]0.050229[/C][C]0.522[/C][C]0.301371[/C][/ROW]
[ROW][C]23[/C][C]-0.035213[/C][C]-0.3659[/C][C]0.357561[/C][/ROW]
[ROW][C]24[/C][C]-0.00795[/C][C]-0.0826[/C][C]0.467155[/C][/ROW]
[ROW][C]25[/C][C]-0.0268[/C][C]-0.2785[/C][C]0.390575[/C][/ROW]
[ROW][C]26[/C][C]-0.105293[/C][C]-1.0942[/C][C]0.138142[/C][/ROW]
[ROW][C]27[/C][C]-0.018486[/C][C]-0.1921[/C][C]0.424008[/C][/ROW]
[ROW][C]28[/C][C]-0.03106[/C][C]-0.3228[/C][C]0.373739[/C][/ROW]
[ROW][C]29[/C][C]-0.091883[/C][C]-0.9549[/C][C]0.170888[/C][/ROW]
[ROW][C]30[/C][C]-0.039979[/C][C]-0.4155[/C][C]0.339308[/C][/ROW]
[ROW][C]31[/C][C]0.044128[/C][C]0.4586[/C][C]0.323724[/C][/ROW]
[ROW][C]32[/C][C]-0.033398[/C][C]-0.3471[/C][C]0.364604[/C][/ROW]
[ROW][C]33[/C][C]-0.051032[/C][C]-0.5303[/C][C]0.298483[/C][/ROW]
[ROW][C]34[/C][C]-0.011435[/C][C]-0.1188[/C][C]0.452812[/C][/ROW]
[ROW][C]35[/C][C]0.018195[/C][C]0.1891[/C][C]0.425189[/C][/ROW]
[ROW][C]36[/C][C]0.046133[/C][C]0.4794[/C][C]0.316302[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60483&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60483&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.98530910.23960
2-0.17296-1.79750.037529
3-0.210631-2.18890.015377
4-0.048562-0.50470.307409
5-0.040217-0.41790.338409
60.0247190.25690.398877
70.0752420.78190.217982
8-0.060717-0.6310.26469
9-0.077918-0.80980.209932
10-0.11544-1.19970.116443
110.0435530.45260.325866
12-0.196007-2.0370.02205
13-0.081421-0.84610.199671
140.0790610.82160.20655
15-0.054165-0.56290.287335
160.0770220.80040.212608
17-0.103338-1.07390.142627
18-0.004543-0.04720.481217
19-0.10603-1.10190.136479
20-0.025839-0.26850.394403
210.088070.91530.181049
220.0502290.5220.301371
23-0.035213-0.36590.357561
24-0.00795-0.08260.467155
25-0.0268-0.27850.390575
26-0.105293-1.09420.138142
27-0.018486-0.19210.424008
28-0.03106-0.32280.373739
29-0.091883-0.95490.170888
30-0.039979-0.41550.339308
310.0441280.45860.323724
32-0.033398-0.34710.364604
33-0.051032-0.53030.298483
34-0.011435-0.11880.452812
350.0181950.18910.425189
360.0461330.47940.316302


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')