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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 computationThu, 03 Dec 2009 03:03:52 -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/Dec/03/t1259834687nng6ycmak2yza64.htm/, Retrieved Thu, 18 Apr 2024 08:06:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62658, Retrieved Thu, 18 Apr 2024 08:06:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-   PD      [(Partial) Autocorrelation Function] [] [2009-12-03 10:03:52] [5858ea01c9bd81debbf921a11363ad90] [Current]
-   P         [(Partial) Autocorrelation Function] [] [2009-12-03 10:05:50] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 10:36:07] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 10:37:59] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 10:39:07] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P         [(Partial) Autocorrelation Function] [] [2009-12-03 10:10:51] [2f674a53c3d7aaa1bcf80e66074d3c9b]
- RMPD        [Variability] [] [2009-12-03 14:53:10] [2f674a53c3d7aaa1bcf80e66074d3c9b]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730

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=62658&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=62658&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62658&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
10.22662.36580.00988
20.0170030.17750.429715
3-0.010589-0.11060.456086
4-0.077449-0.80860.210255
5-0.156139-1.63010.052979
6-0.316535-3.30470.000644
7-0.177953-1.85790.032942
8-0.060659-0.63330.263931
9-0.025432-0.26550.395554
10-0.059867-0.6250.266629
110.182971.91030.029363
120.7972538.32360
130.1447551.51130.066805
14-0.021453-0.2240.411598
15-0.05291-0.55240.290905
16-0.130334-1.36070.088203
17-0.162343-1.69490.046474
18-0.330731-3.45290.000395
19-0.182089-1.90110.029967
20-0.065111-0.67980.249042
21-0.076834-0.80220.212099
22-0.068353-0.71360.238491
230.174341.82020.035739
240.6841877.14310
250.1556051.62460.053572
260.0085380.08910.464567
27-0.041799-0.43640.331706
28-0.087848-0.91720.180541
29-0.115791-1.20890.11466
30-0.282084-2.9450.001974
31-0.128633-1.3430.091036
32-0.059253-0.61860.268729
33-0.067721-0.7070.240528
34-0.044201-0.46150.322692
350.1520151.58710.057695
360.5463855.70440

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.2266 & 2.3658 & 0.00988 \tabularnewline
2 & 0.017003 & 0.1775 & 0.429715 \tabularnewline
3 & -0.010589 & -0.1106 & 0.456086 \tabularnewline
4 & -0.077449 & -0.8086 & 0.210255 \tabularnewline
5 & -0.156139 & -1.6301 & 0.052979 \tabularnewline
6 & -0.316535 & -3.3047 & 0.000644 \tabularnewline
7 & -0.177953 & -1.8579 & 0.032942 \tabularnewline
8 & -0.060659 & -0.6333 & 0.263931 \tabularnewline
9 & -0.025432 & -0.2655 & 0.395554 \tabularnewline
10 & -0.059867 & -0.625 & 0.266629 \tabularnewline
11 & 0.18297 & 1.9103 & 0.029363 \tabularnewline
12 & 0.797253 & 8.3236 & 0 \tabularnewline
13 & 0.144755 & 1.5113 & 0.066805 \tabularnewline
14 & -0.021453 & -0.224 & 0.411598 \tabularnewline
15 & -0.05291 & -0.5524 & 0.290905 \tabularnewline
16 & -0.130334 & -1.3607 & 0.088203 \tabularnewline
17 & -0.162343 & -1.6949 & 0.046474 \tabularnewline
18 & -0.330731 & -3.4529 & 0.000395 \tabularnewline
19 & -0.182089 & -1.9011 & 0.029967 \tabularnewline
20 & -0.065111 & -0.6798 & 0.249042 \tabularnewline
21 & -0.076834 & -0.8022 & 0.212099 \tabularnewline
22 & -0.068353 & -0.7136 & 0.238491 \tabularnewline
23 & 0.17434 & 1.8202 & 0.035739 \tabularnewline
24 & 0.684187 & 7.1431 & 0 \tabularnewline
25 & 0.155605 & 1.6246 & 0.053572 \tabularnewline
26 & 0.008538 & 0.0891 & 0.464567 \tabularnewline
27 & -0.041799 & -0.4364 & 0.331706 \tabularnewline
28 & -0.087848 & -0.9172 & 0.180541 \tabularnewline
29 & -0.115791 & -1.2089 & 0.11466 \tabularnewline
30 & -0.282084 & -2.945 & 0.001974 \tabularnewline
31 & -0.128633 & -1.343 & 0.091036 \tabularnewline
32 & -0.059253 & -0.6186 & 0.268729 \tabularnewline
33 & -0.067721 & -0.707 & 0.240528 \tabularnewline
34 & -0.044201 & -0.4615 & 0.322692 \tabularnewline
35 & 0.152015 & 1.5871 & 0.057695 \tabularnewline
36 & 0.546385 & 5.7044 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62658&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]0.2266[/C][C]2.3658[/C][C]0.00988[/C][/ROW]
[ROW][C]2[/C][C]0.017003[/C][C]0.1775[/C][C]0.429715[/C][/ROW]
[ROW][C]3[/C][C]-0.010589[/C][C]-0.1106[/C][C]0.456086[/C][/ROW]
[ROW][C]4[/C][C]-0.077449[/C][C]-0.8086[/C][C]0.210255[/C][/ROW]
[ROW][C]5[/C][C]-0.156139[/C][C]-1.6301[/C][C]0.052979[/C][/ROW]
[ROW][C]6[/C][C]-0.316535[/C][C]-3.3047[/C][C]0.000644[/C][/ROW]
[ROW][C]7[/C][C]-0.177953[/C][C]-1.8579[/C][C]0.032942[/C][/ROW]
[ROW][C]8[/C][C]-0.060659[/C][C]-0.6333[/C][C]0.263931[/C][/ROW]
[ROW][C]9[/C][C]-0.025432[/C][C]-0.2655[/C][C]0.395554[/C][/ROW]
[ROW][C]10[/C][C]-0.059867[/C][C]-0.625[/C][C]0.266629[/C][/ROW]
[ROW][C]11[/C][C]0.18297[/C][C]1.9103[/C][C]0.029363[/C][/ROW]
[ROW][C]12[/C][C]0.797253[/C][C]8.3236[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.144755[/C][C]1.5113[/C][C]0.066805[/C][/ROW]
[ROW][C]14[/C][C]-0.021453[/C][C]-0.224[/C][C]0.411598[/C][/ROW]
[ROW][C]15[/C][C]-0.05291[/C][C]-0.5524[/C][C]0.290905[/C][/ROW]
[ROW][C]16[/C][C]-0.130334[/C][C]-1.3607[/C][C]0.088203[/C][/ROW]
[ROW][C]17[/C][C]-0.162343[/C][C]-1.6949[/C][C]0.046474[/C][/ROW]
[ROW][C]18[/C][C]-0.330731[/C][C]-3.4529[/C][C]0.000395[/C][/ROW]
[ROW][C]19[/C][C]-0.182089[/C][C]-1.9011[/C][C]0.029967[/C][/ROW]
[ROW][C]20[/C][C]-0.065111[/C][C]-0.6798[/C][C]0.249042[/C][/ROW]
[ROW][C]21[/C][C]-0.076834[/C][C]-0.8022[/C][C]0.212099[/C][/ROW]
[ROW][C]22[/C][C]-0.068353[/C][C]-0.7136[/C][C]0.238491[/C][/ROW]
[ROW][C]23[/C][C]0.17434[/C][C]1.8202[/C][C]0.035739[/C][/ROW]
[ROW][C]24[/C][C]0.684187[/C][C]7.1431[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.155605[/C][C]1.6246[/C][C]0.053572[/C][/ROW]
[ROW][C]26[/C][C]0.008538[/C][C]0.0891[/C][C]0.464567[/C][/ROW]
[ROW][C]27[/C][C]-0.041799[/C][C]-0.4364[/C][C]0.331706[/C][/ROW]
[ROW][C]28[/C][C]-0.087848[/C][C]-0.9172[/C][C]0.180541[/C][/ROW]
[ROW][C]29[/C][C]-0.115791[/C][C]-1.2089[/C][C]0.11466[/C][/ROW]
[ROW][C]30[/C][C]-0.282084[/C][C]-2.945[/C][C]0.001974[/C][/ROW]
[ROW][C]31[/C][C]-0.128633[/C][C]-1.343[/C][C]0.091036[/C][/ROW]
[ROW][C]32[/C][C]-0.059253[/C][C]-0.6186[/C][C]0.268729[/C][/ROW]
[ROW][C]33[/C][C]-0.067721[/C][C]-0.707[/C][C]0.240528[/C][/ROW]
[ROW][C]34[/C][C]-0.044201[/C][C]-0.4615[/C][C]0.322692[/C][/ROW]
[ROW][C]35[/C][C]0.152015[/C][C]1.5871[/C][C]0.057695[/C][/ROW]
[ROW][C]36[/C][C]0.546385[/C][C]5.7044[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62658&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62658&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
10.22662.36580.00988
20.0170030.17750.429715
3-0.010589-0.11060.456086
4-0.077449-0.80860.210255
5-0.156139-1.63010.052979
6-0.316535-3.30470.000644
7-0.177953-1.85790.032942
8-0.060659-0.63330.263931
9-0.025432-0.26550.395554
10-0.059867-0.6250.266629
110.182971.91030.029363
120.7972538.32360
130.1447551.51130.066805
14-0.021453-0.2240.411598
15-0.05291-0.55240.290905
16-0.130334-1.36070.088203
17-0.162343-1.69490.046474
18-0.330731-3.45290.000395
19-0.182089-1.90110.029967
20-0.065111-0.67980.249042
21-0.076834-0.80220.212099
22-0.068353-0.71360.238491
230.174341.82020.035739
240.6841877.14310
250.1556051.62460.053572
260.0085380.08910.464567
27-0.041799-0.43640.331706
28-0.087848-0.91720.180541
29-0.115791-1.20890.11466
30-0.282084-2.9450.001974
31-0.128633-1.3430.091036
32-0.059253-0.61860.268729
33-0.067721-0.7070.240528
34-0.044201-0.46150.322692
350.1520151.58710.057695
360.5463855.70440






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.22662.36580.00988
2-0.036203-0.3780.353094
3-0.006732-0.07030.472048
4-0.076899-0.80280.211905
5-0.128667-1.34330.090978
6-0.274561-2.86650.002491
7-0.07285-0.76060.224277
8-0.036471-0.38080.352057
9-0.039951-0.41710.338713
10-0.121759-1.27120.103181
110.1520741.58770.057626
120.7621937.95750
13-0.301994-3.15290.001044
14-0.187328-1.95580.026526
15-0.023412-0.24440.403681
16-0.086704-0.90520.183675
17-0.035909-0.37490.354231
18-0.022593-0.23590.406984
190.0159660.16670.433959
20-0.112098-1.17030.12221
21-0.136639-1.42660.078284
220.1741511.81820.035891
230.0146750.15320.439258
240.0316710.33070.370771
250.1183681.23580.109595
260.0061030.06370.474656
27-0.062639-0.6540.257255
280.1260511.3160.095466
290.0657460.68640.246956
30-0.004297-0.04490.482151
310.0095550.09980.46036
32-0.049837-0.52030.301949
330.060280.62930.265221
340.0054550.0570.477343
35-0.056988-0.5950.276548
36-0.132888-1.38740.084077

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.2266 & 2.3658 & 0.00988 \tabularnewline
2 & -0.036203 & -0.378 & 0.353094 \tabularnewline
3 & -0.006732 & -0.0703 & 0.472048 \tabularnewline
4 & -0.076899 & -0.8028 & 0.211905 \tabularnewline
5 & -0.128667 & -1.3433 & 0.090978 \tabularnewline
6 & -0.274561 & -2.8665 & 0.002491 \tabularnewline
7 & -0.07285 & -0.7606 & 0.224277 \tabularnewline
8 & -0.036471 & -0.3808 & 0.352057 \tabularnewline
9 & -0.039951 & -0.4171 & 0.338713 \tabularnewline
10 & -0.121759 & -1.2712 & 0.103181 \tabularnewline
11 & 0.152074 & 1.5877 & 0.057626 \tabularnewline
12 & 0.762193 & 7.9575 & 0 \tabularnewline
13 & -0.301994 & -3.1529 & 0.001044 \tabularnewline
14 & -0.187328 & -1.9558 & 0.026526 \tabularnewline
15 & -0.023412 & -0.2444 & 0.403681 \tabularnewline
16 & -0.086704 & -0.9052 & 0.183675 \tabularnewline
17 & -0.035909 & -0.3749 & 0.354231 \tabularnewline
18 & -0.022593 & -0.2359 & 0.406984 \tabularnewline
19 & 0.015966 & 0.1667 & 0.433959 \tabularnewline
20 & -0.112098 & -1.1703 & 0.12221 \tabularnewline
21 & -0.136639 & -1.4266 & 0.078284 \tabularnewline
22 & 0.174151 & 1.8182 & 0.035891 \tabularnewline
23 & 0.014675 & 0.1532 & 0.439258 \tabularnewline
24 & 0.031671 & 0.3307 & 0.370771 \tabularnewline
25 & 0.118368 & 1.2358 & 0.109595 \tabularnewline
26 & 0.006103 & 0.0637 & 0.474656 \tabularnewline
27 & -0.062639 & -0.654 & 0.257255 \tabularnewline
28 & 0.126051 & 1.316 & 0.095466 \tabularnewline
29 & 0.065746 & 0.6864 & 0.246956 \tabularnewline
30 & -0.004297 & -0.0449 & 0.482151 \tabularnewline
31 & 0.009555 & 0.0998 & 0.46036 \tabularnewline
32 & -0.049837 & -0.5203 & 0.301949 \tabularnewline
33 & 0.06028 & 0.6293 & 0.265221 \tabularnewline
34 & 0.005455 & 0.057 & 0.477343 \tabularnewline
35 & -0.056988 & -0.595 & 0.276548 \tabularnewline
36 & -0.132888 & -1.3874 & 0.084077 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62658&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]0.2266[/C][C]2.3658[/C][C]0.00988[/C][/ROW]
[ROW][C]2[/C][C]-0.036203[/C][C]-0.378[/C][C]0.353094[/C][/ROW]
[ROW][C]3[/C][C]-0.006732[/C][C]-0.0703[/C][C]0.472048[/C][/ROW]
[ROW][C]4[/C][C]-0.076899[/C][C]-0.8028[/C][C]0.211905[/C][/ROW]
[ROW][C]5[/C][C]-0.128667[/C][C]-1.3433[/C][C]0.090978[/C][/ROW]
[ROW][C]6[/C][C]-0.274561[/C][C]-2.8665[/C][C]0.002491[/C][/ROW]
[ROW][C]7[/C][C]-0.07285[/C][C]-0.7606[/C][C]0.224277[/C][/ROW]
[ROW][C]8[/C][C]-0.036471[/C][C]-0.3808[/C][C]0.352057[/C][/ROW]
[ROW][C]9[/C][C]-0.039951[/C][C]-0.4171[/C][C]0.338713[/C][/ROW]
[ROW][C]10[/C][C]-0.121759[/C][C]-1.2712[/C][C]0.103181[/C][/ROW]
[ROW][C]11[/C][C]0.152074[/C][C]1.5877[/C][C]0.057626[/C][/ROW]
[ROW][C]12[/C][C]0.762193[/C][C]7.9575[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.301994[/C][C]-3.1529[/C][C]0.001044[/C][/ROW]
[ROW][C]14[/C][C]-0.187328[/C][C]-1.9558[/C][C]0.026526[/C][/ROW]
[ROW][C]15[/C][C]-0.023412[/C][C]-0.2444[/C][C]0.403681[/C][/ROW]
[ROW][C]16[/C][C]-0.086704[/C][C]-0.9052[/C][C]0.183675[/C][/ROW]
[ROW][C]17[/C][C]-0.035909[/C][C]-0.3749[/C][C]0.354231[/C][/ROW]
[ROW][C]18[/C][C]-0.022593[/C][C]-0.2359[/C][C]0.406984[/C][/ROW]
[ROW][C]19[/C][C]0.015966[/C][C]0.1667[/C][C]0.433959[/C][/ROW]
[ROW][C]20[/C][C]-0.112098[/C][C]-1.1703[/C][C]0.12221[/C][/ROW]
[ROW][C]21[/C][C]-0.136639[/C][C]-1.4266[/C][C]0.078284[/C][/ROW]
[ROW][C]22[/C][C]0.174151[/C][C]1.8182[/C][C]0.035891[/C][/ROW]
[ROW][C]23[/C][C]0.014675[/C][C]0.1532[/C][C]0.439258[/C][/ROW]
[ROW][C]24[/C][C]0.031671[/C][C]0.3307[/C][C]0.370771[/C][/ROW]
[ROW][C]25[/C][C]0.118368[/C][C]1.2358[/C][C]0.109595[/C][/ROW]
[ROW][C]26[/C][C]0.006103[/C][C]0.0637[/C][C]0.474656[/C][/ROW]
[ROW][C]27[/C][C]-0.062639[/C][C]-0.654[/C][C]0.257255[/C][/ROW]
[ROW][C]28[/C][C]0.126051[/C][C]1.316[/C][C]0.095466[/C][/ROW]
[ROW][C]29[/C][C]0.065746[/C][C]0.6864[/C][C]0.246956[/C][/ROW]
[ROW][C]30[/C][C]-0.004297[/C][C]-0.0449[/C][C]0.482151[/C][/ROW]
[ROW][C]31[/C][C]0.009555[/C][C]0.0998[/C][C]0.46036[/C][/ROW]
[ROW][C]32[/C][C]-0.049837[/C][C]-0.5203[/C][C]0.301949[/C][/ROW]
[ROW][C]33[/C][C]0.06028[/C][C]0.6293[/C][C]0.265221[/C][/ROW]
[ROW][C]34[/C][C]0.005455[/C][C]0.057[/C][C]0.477343[/C][/ROW]
[ROW][C]35[/C][C]-0.056988[/C][C]-0.595[/C][C]0.276548[/C][/ROW]
[ROW][C]36[/C][C]-0.132888[/C][C]-1.3874[/C][C]0.084077[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62658&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62658&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
10.22662.36580.00988
2-0.036203-0.3780.353094
3-0.006732-0.07030.472048
4-0.076899-0.80280.211905
5-0.128667-1.34330.090978
6-0.274561-2.86650.002491
7-0.07285-0.76060.224277
8-0.036471-0.38080.352057
9-0.039951-0.41710.338713
10-0.121759-1.27120.103181
110.1520741.58770.057626
120.7621937.95750
13-0.301994-3.15290.001044
14-0.187328-1.95580.026526
15-0.023412-0.24440.403681
16-0.086704-0.90520.183675
17-0.035909-0.37490.354231
18-0.022593-0.23590.406984
190.0159660.16670.433959
20-0.112098-1.17030.12221
21-0.136639-1.42660.078284
220.1741511.81820.035891
230.0146750.15320.439258
240.0316710.33070.370771
250.1183681.23580.109595
260.0061030.06370.474656
27-0.062639-0.6540.257255
280.1260511.3160.095466
290.0657460.68640.246956
30-0.004297-0.04490.482151
310.0095550.09980.46036
32-0.049837-0.52030.301949
330.060280.62930.265221
340.0054550.0570.477343
35-0.056988-0.5950.276548
36-0.132888-1.38740.084077


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.5 ; 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')