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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 computationThu, 26 Nov 2009 17:21:06 -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/t1259281499iblpwfiuymgbdoz.htm/, Retrieved Mon, 29 Apr 2024 07:35:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60452, Retrieved Mon, 29 Apr 2024 07:35:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact204
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]
-   PD          [(Partial) Autocorrelation Function] [] [2009-11-27 00:21:06] [90c9838c596c9c0a7d0d4c412ffe5b98] [Current]
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Dataseries X:
6802.96
7132.68
7073.29
7264.5
7105.33
7218.71
7225.72
7354.25
7745.46
8070.26
8366.33
8667.51
8854.34
9218.1
9332.9
9358.31
9248.66
9401.2
9652.04
9957.38
10110.63
10169.26
10343.78
10750.21
11337.5
11786.96
12083.04
12007.74
11745.93
11051.51
11445.9
11924.88
12247.63
12690.91
12910.7
13202.12
13654.67
13862.82
13523.93
14211.17
14510.35
14289.23
14111.82
13086.59
13351.54
13747.69
12855.61
12926.93
12121.95
11731.65
11639.51
12163.78
12029.53
11234.18
9852.13
9709.04
9332.75
7108.6
6691.49
6143.05




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=60452&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=60452&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60452&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0255050.17490.430973
2-0.094046-0.64470.261113
30.1768571.21250.115696
4-0.064439-0.44180.330341
50.2256281.54680.064306
60.132370.90750.18439
7-0.111745-0.76610.223729
80.1905361.30630.098912
90.1013140.69460.245371
100.024990.17130.432352
110.2286291.56740.061865
12-0.196156-1.34480.092575
13-0.056201-0.38530.350878
140.2377561.630.054896
15-0.01515-0.10390.458861
16-0.007531-0.05160.479522
17-0.06698-0.45920.324107
18-0.137721-0.94420.174957
190.0610160.41830.338814
20-0.058157-0.39870.345958
21-0.029801-0.20430.419499
22-0.016683-0.11440.454713
23-0.047786-0.32760.372333
24-0.12646-0.8670.195182
25-0.017702-0.12140.451963
26-0.087411-0.59930.275938
27-0.035835-0.24570.403503
280.0484260.3320.370687
29-0.113475-0.77790.22025
30-0.089556-0.6140.2711
31-0.04815-0.33010.371396
32-0.049555-0.33970.367787
33-0.094006-0.64450.261201
34-0.058164-0.39880.34594
35-0.06692-0.45880.324253
360.0001379e-040.499627

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.025505 & 0.1749 & 0.430973 \tabularnewline
2 & -0.094046 & -0.6447 & 0.261113 \tabularnewline
3 & 0.176857 & 1.2125 & 0.115696 \tabularnewline
4 & -0.064439 & -0.4418 & 0.330341 \tabularnewline
5 & 0.225628 & 1.5468 & 0.064306 \tabularnewline
6 & 0.13237 & 0.9075 & 0.18439 \tabularnewline
7 & -0.111745 & -0.7661 & 0.223729 \tabularnewline
8 & 0.190536 & 1.3063 & 0.098912 \tabularnewline
9 & 0.101314 & 0.6946 & 0.245371 \tabularnewline
10 & 0.02499 & 0.1713 & 0.432352 \tabularnewline
11 & 0.228629 & 1.5674 & 0.061865 \tabularnewline
12 & -0.196156 & -1.3448 & 0.092575 \tabularnewline
13 & -0.056201 & -0.3853 & 0.350878 \tabularnewline
14 & 0.237756 & 1.63 & 0.054896 \tabularnewline
15 & -0.01515 & -0.1039 & 0.458861 \tabularnewline
16 & -0.007531 & -0.0516 & 0.479522 \tabularnewline
17 & -0.06698 & -0.4592 & 0.324107 \tabularnewline
18 & -0.137721 & -0.9442 & 0.174957 \tabularnewline
19 & 0.061016 & 0.4183 & 0.338814 \tabularnewline
20 & -0.058157 & -0.3987 & 0.345958 \tabularnewline
21 & -0.029801 & -0.2043 & 0.419499 \tabularnewline
22 & -0.016683 & -0.1144 & 0.454713 \tabularnewline
23 & -0.047786 & -0.3276 & 0.372333 \tabularnewline
24 & -0.12646 & -0.867 & 0.195182 \tabularnewline
25 & -0.017702 & -0.1214 & 0.451963 \tabularnewline
26 & -0.087411 & -0.5993 & 0.275938 \tabularnewline
27 & -0.035835 & -0.2457 & 0.403503 \tabularnewline
28 & 0.048426 & 0.332 & 0.370687 \tabularnewline
29 & -0.113475 & -0.7779 & 0.22025 \tabularnewline
30 & -0.089556 & -0.614 & 0.2711 \tabularnewline
31 & -0.04815 & -0.3301 & 0.371396 \tabularnewline
32 & -0.049555 & -0.3397 & 0.367787 \tabularnewline
33 & -0.094006 & -0.6445 & 0.261201 \tabularnewline
34 & -0.058164 & -0.3988 & 0.34594 \tabularnewline
35 & -0.06692 & -0.4588 & 0.324253 \tabularnewline
36 & 0.000137 & 9e-04 & 0.499627 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60452&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]0.025505[/C][C]0.1749[/C][C]0.430973[/C][/ROW]
[ROW][C]2[/C][C]-0.094046[/C][C]-0.6447[/C][C]0.261113[/C][/ROW]
[ROW][C]3[/C][C]0.176857[/C][C]1.2125[/C][C]0.115696[/C][/ROW]
[ROW][C]4[/C][C]-0.064439[/C][C]-0.4418[/C][C]0.330341[/C][/ROW]
[ROW][C]5[/C][C]0.225628[/C][C]1.5468[/C][C]0.064306[/C][/ROW]
[ROW][C]6[/C][C]0.13237[/C][C]0.9075[/C][C]0.18439[/C][/ROW]
[ROW][C]7[/C][C]-0.111745[/C][C]-0.7661[/C][C]0.223729[/C][/ROW]
[ROW][C]8[/C][C]0.190536[/C][C]1.3063[/C][C]0.098912[/C][/ROW]
[ROW][C]9[/C][C]0.101314[/C][C]0.6946[/C][C]0.245371[/C][/ROW]
[ROW][C]10[/C][C]0.02499[/C][C]0.1713[/C][C]0.432352[/C][/ROW]
[ROW][C]11[/C][C]0.228629[/C][C]1.5674[/C][C]0.061865[/C][/ROW]
[ROW][C]12[/C][C]-0.196156[/C][C]-1.3448[/C][C]0.092575[/C][/ROW]
[ROW][C]13[/C][C]-0.056201[/C][C]-0.3853[/C][C]0.350878[/C][/ROW]
[ROW][C]14[/C][C]0.237756[/C][C]1.63[/C][C]0.054896[/C][/ROW]
[ROW][C]15[/C][C]-0.01515[/C][C]-0.1039[/C][C]0.458861[/C][/ROW]
[ROW][C]16[/C][C]-0.007531[/C][C]-0.0516[/C][C]0.479522[/C][/ROW]
[ROW][C]17[/C][C]-0.06698[/C][C]-0.4592[/C][C]0.324107[/C][/ROW]
[ROW][C]18[/C][C]-0.137721[/C][C]-0.9442[/C][C]0.174957[/C][/ROW]
[ROW][C]19[/C][C]0.061016[/C][C]0.4183[/C][C]0.338814[/C][/ROW]
[ROW][C]20[/C][C]-0.058157[/C][C]-0.3987[/C][C]0.345958[/C][/ROW]
[ROW][C]21[/C][C]-0.029801[/C][C]-0.2043[/C][C]0.419499[/C][/ROW]
[ROW][C]22[/C][C]-0.016683[/C][C]-0.1144[/C][C]0.454713[/C][/ROW]
[ROW][C]23[/C][C]-0.047786[/C][C]-0.3276[/C][C]0.372333[/C][/ROW]
[ROW][C]24[/C][C]-0.12646[/C][C]-0.867[/C][C]0.195182[/C][/ROW]
[ROW][C]25[/C][C]-0.017702[/C][C]-0.1214[/C][C]0.451963[/C][/ROW]
[ROW][C]26[/C][C]-0.087411[/C][C]-0.5993[/C][C]0.275938[/C][/ROW]
[ROW][C]27[/C][C]-0.035835[/C][C]-0.2457[/C][C]0.403503[/C][/ROW]
[ROW][C]28[/C][C]0.048426[/C][C]0.332[/C][C]0.370687[/C][/ROW]
[ROW][C]29[/C][C]-0.113475[/C][C]-0.7779[/C][C]0.22025[/C][/ROW]
[ROW][C]30[/C][C]-0.089556[/C][C]-0.614[/C][C]0.2711[/C][/ROW]
[ROW][C]31[/C][C]-0.04815[/C][C]-0.3301[/C][C]0.371396[/C][/ROW]
[ROW][C]32[/C][C]-0.049555[/C][C]-0.3397[/C][C]0.367787[/C][/ROW]
[ROW][C]33[/C][C]-0.094006[/C][C]-0.6445[/C][C]0.261201[/C][/ROW]
[ROW][C]34[/C][C]-0.058164[/C][C]-0.3988[/C][C]0.34594[/C][/ROW]
[ROW][C]35[/C][C]-0.06692[/C][C]-0.4588[/C][C]0.324253[/C][/ROW]
[ROW][C]36[/C][C]0.000137[/C][C]9e-04[/C][C]0.499627[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60452&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60452&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0255050.17490.430973
2-0.094046-0.64470.261113
30.1768571.21250.115696
4-0.064439-0.44180.330341
50.2256281.54680.064306
60.132370.90750.18439
7-0.111745-0.76610.223729
80.1905361.30630.098912
90.1013140.69460.245371
100.024990.17130.432352
110.2286291.56740.061865
12-0.196156-1.34480.092575
13-0.056201-0.38530.350878
140.2377561.630.054896
15-0.01515-0.10390.458861
16-0.007531-0.05160.479522
17-0.06698-0.45920.324107
18-0.137721-0.94420.174957
190.0610160.41830.338814
20-0.058157-0.39870.345958
21-0.029801-0.20430.419499
22-0.016683-0.11440.454713
23-0.047786-0.32760.372333
24-0.12646-0.8670.195182
25-0.017702-0.12140.451963
26-0.087411-0.59930.275938
27-0.035835-0.24570.403503
280.0484260.3320.370687
29-0.113475-0.77790.22025
30-0.089556-0.6140.2711
31-0.04815-0.33010.371396
32-0.049555-0.33970.367787
33-0.094006-0.64450.261201
34-0.058164-0.39880.34594
35-0.06692-0.45880.324253
360.0001379e-040.499627







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0255050.17490.430973
2-0.094758-0.64960.259547
30.1836681.25920.107095
4-0.090425-0.61990.269152
50.2832531.94190.029079
60.052840.36230.359393
7-0.034788-0.23850.406267
80.1428060.9790.166289
90.069590.47710.317755
100.0500760.34330.366451
110.1545981.05990.14731
12-0.221791-1.52050.067539
13-0.041999-0.28790.387332
140.0784230.53760.29668
150.027130.1860.426625
16-0.09435-0.64680.260444
17-0.106465-0.72990.234541
18-0.083315-0.57120.285299
19-0.087748-0.60160.275176
20-0.094274-0.64630.260611
210.0827240.56710.286664
22-0.088107-0.6040.274364
230.0982530.67360.251936
24-0.216642-1.48520.072081
250.0189260.12970.448659
26-0.050211-0.34420.366105
270.1340240.91880.181441
280.0550240.37720.353852
29-0.050989-0.34960.364115
30-0.097526-0.66860.253509
310.0046530.03190.487343
32-0.015749-0.1080.457239
33-0.035559-0.24380.40423
34-0.036983-0.25350.400477
350.0138420.09490.462399
36-0.06793-0.46570.321789

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.025505 & 0.1749 & 0.430973 \tabularnewline
2 & -0.094758 & -0.6496 & 0.259547 \tabularnewline
3 & 0.183668 & 1.2592 & 0.107095 \tabularnewline
4 & -0.090425 & -0.6199 & 0.269152 \tabularnewline
5 & 0.283253 & 1.9419 & 0.029079 \tabularnewline
6 & 0.05284 & 0.3623 & 0.359393 \tabularnewline
7 & -0.034788 & -0.2385 & 0.406267 \tabularnewline
8 & 0.142806 & 0.979 & 0.166289 \tabularnewline
9 & 0.06959 & 0.4771 & 0.317755 \tabularnewline
10 & 0.050076 & 0.3433 & 0.366451 \tabularnewline
11 & 0.154598 & 1.0599 & 0.14731 \tabularnewline
12 & -0.221791 & -1.5205 & 0.067539 \tabularnewline
13 & -0.041999 & -0.2879 & 0.387332 \tabularnewline
14 & 0.078423 & 0.5376 & 0.29668 \tabularnewline
15 & 0.02713 & 0.186 & 0.426625 \tabularnewline
16 & -0.09435 & -0.6468 & 0.260444 \tabularnewline
17 & -0.106465 & -0.7299 & 0.234541 \tabularnewline
18 & -0.083315 & -0.5712 & 0.285299 \tabularnewline
19 & -0.087748 & -0.6016 & 0.275176 \tabularnewline
20 & -0.094274 & -0.6463 & 0.260611 \tabularnewline
21 & 0.082724 & 0.5671 & 0.286664 \tabularnewline
22 & -0.088107 & -0.604 & 0.274364 \tabularnewline
23 & 0.098253 & 0.6736 & 0.251936 \tabularnewline
24 & -0.216642 & -1.4852 & 0.072081 \tabularnewline
25 & 0.018926 & 0.1297 & 0.448659 \tabularnewline
26 & -0.050211 & -0.3442 & 0.366105 \tabularnewline
27 & 0.134024 & 0.9188 & 0.181441 \tabularnewline
28 & 0.055024 & 0.3772 & 0.353852 \tabularnewline
29 & -0.050989 & -0.3496 & 0.364115 \tabularnewline
30 & -0.097526 & -0.6686 & 0.253509 \tabularnewline
31 & 0.004653 & 0.0319 & 0.487343 \tabularnewline
32 & -0.015749 & -0.108 & 0.457239 \tabularnewline
33 & -0.035559 & -0.2438 & 0.40423 \tabularnewline
34 & -0.036983 & -0.2535 & 0.400477 \tabularnewline
35 & 0.013842 & 0.0949 & 0.462399 \tabularnewline
36 & -0.06793 & -0.4657 & 0.321789 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60452&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]0.025505[/C][C]0.1749[/C][C]0.430973[/C][/ROW]
[ROW][C]2[/C][C]-0.094758[/C][C]-0.6496[/C][C]0.259547[/C][/ROW]
[ROW][C]3[/C][C]0.183668[/C][C]1.2592[/C][C]0.107095[/C][/ROW]
[ROW][C]4[/C][C]-0.090425[/C][C]-0.6199[/C][C]0.269152[/C][/ROW]
[ROW][C]5[/C][C]0.283253[/C][C]1.9419[/C][C]0.029079[/C][/ROW]
[ROW][C]6[/C][C]0.05284[/C][C]0.3623[/C][C]0.359393[/C][/ROW]
[ROW][C]7[/C][C]-0.034788[/C][C]-0.2385[/C][C]0.406267[/C][/ROW]
[ROW][C]8[/C][C]0.142806[/C][C]0.979[/C][C]0.166289[/C][/ROW]
[ROW][C]9[/C][C]0.06959[/C][C]0.4771[/C][C]0.317755[/C][/ROW]
[ROW][C]10[/C][C]0.050076[/C][C]0.3433[/C][C]0.366451[/C][/ROW]
[ROW][C]11[/C][C]0.154598[/C][C]1.0599[/C][C]0.14731[/C][/ROW]
[ROW][C]12[/C][C]-0.221791[/C][C]-1.5205[/C][C]0.067539[/C][/ROW]
[ROW][C]13[/C][C]-0.041999[/C][C]-0.2879[/C][C]0.387332[/C][/ROW]
[ROW][C]14[/C][C]0.078423[/C][C]0.5376[/C][C]0.29668[/C][/ROW]
[ROW][C]15[/C][C]0.02713[/C][C]0.186[/C][C]0.426625[/C][/ROW]
[ROW][C]16[/C][C]-0.09435[/C][C]-0.6468[/C][C]0.260444[/C][/ROW]
[ROW][C]17[/C][C]-0.106465[/C][C]-0.7299[/C][C]0.234541[/C][/ROW]
[ROW][C]18[/C][C]-0.083315[/C][C]-0.5712[/C][C]0.285299[/C][/ROW]
[ROW][C]19[/C][C]-0.087748[/C][C]-0.6016[/C][C]0.275176[/C][/ROW]
[ROW][C]20[/C][C]-0.094274[/C][C]-0.6463[/C][C]0.260611[/C][/ROW]
[ROW][C]21[/C][C]0.082724[/C][C]0.5671[/C][C]0.286664[/C][/ROW]
[ROW][C]22[/C][C]-0.088107[/C][C]-0.604[/C][C]0.274364[/C][/ROW]
[ROW][C]23[/C][C]0.098253[/C][C]0.6736[/C][C]0.251936[/C][/ROW]
[ROW][C]24[/C][C]-0.216642[/C][C]-1.4852[/C][C]0.072081[/C][/ROW]
[ROW][C]25[/C][C]0.018926[/C][C]0.1297[/C][C]0.448659[/C][/ROW]
[ROW][C]26[/C][C]-0.050211[/C][C]-0.3442[/C][C]0.366105[/C][/ROW]
[ROW][C]27[/C][C]0.134024[/C][C]0.9188[/C][C]0.181441[/C][/ROW]
[ROW][C]28[/C][C]0.055024[/C][C]0.3772[/C][C]0.353852[/C][/ROW]
[ROW][C]29[/C][C]-0.050989[/C][C]-0.3496[/C][C]0.364115[/C][/ROW]
[ROW][C]30[/C][C]-0.097526[/C][C]-0.6686[/C][C]0.253509[/C][/ROW]
[ROW][C]31[/C][C]0.004653[/C][C]0.0319[/C][C]0.487343[/C][/ROW]
[ROW][C]32[/C][C]-0.015749[/C][C]-0.108[/C][C]0.457239[/C][/ROW]
[ROW][C]33[/C][C]-0.035559[/C][C]-0.2438[/C][C]0.40423[/C][/ROW]
[ROW][C]34[/C][C]-0.036983[/C][C]-0.2535[/C][C]0.400477[/C][/ROW]
[ROW][C]35[/C][C]0.013842[/C][C]0.0949[/C][C]0.462399[/C][/ROW]
[ROW][C]36[/C][C]-0.06793[/C][C]-0.4657[/C][C]0.321789[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60452&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60452&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0255050.17490.430973
2-0.094758-0.64960.259547
30.1836681.25920.107095
4-0.090425-0.61990.269152
50.2832531.94190.029079
60.052840.36230.359393
7-0.034788-0.23850.406267
80.1428060.9790.166289
90.069590.47710.317755
100.0500760.34330.366451
110.1545981.05990.14731
12-0.221791-1.52050.067539
13-0.041999-0.28790.387332
140.0784230.53760.29668
150.027130.1860.426625
16-0.09435-0.64680.260444
17-0.106465-0.72990.234541
18-0.083315-0.57120.285299
19-0.087748-0.60160.275176
20-0.094274-0.64630.260611
210.0827240.56710.286664
22-0.088107-0.6040.274364
230.0982530.67360.251936
24-0.216642-1.48520.072081
250.0189260.12970.448659
26-0.050211-0.34420.366105
270.1340240.91880.181441
280.0550240.37720.353852
29-0.050989-0.34960.364115
30-0.097526-0.66860.253509
310.0046530.03190.487343
32-0.015749-0.1080.457239
33-0.035559-0.24380.40423
34-0.036983-0.25350.400477
350.0138420.09490.462399
36-0.06793-0.46570.321789



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')