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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 computationWed, 26 Nov 2014 12:31:13 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/26/t14170050881j070aichor96nr.htm/, Retrieved Sat, 23 May 2026 02:19:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=258923, Retrieved Sat, 23 May 2026 02:19:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact330

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] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [(Partial) Autocorrelation Function] [WS9] [2014-11-26 12:01:09] [074b0dbc8d3b700fa15927150828e345]
- R P       [(Partial) Autocorrelation Function] [WS9] [2014-11-26 12:31:13] [f37066d0c2d3549c99d3204e671bd762] [Current]
-   P         [(Partial) Autocorrelation Function] [WS9] [2014-11-26 12:44:08] [074b0dbc8d3b700fa15927150828e345]
- RMP         [Standard Deviation-Mean Plot] [WS9] [2014-11-26 13:00:01] [074b0dbc8d3b700fa15927150828e345]
- RMP         [ARIMA Backward Selection] [WS9] [2014-11-26 13:48:47] [074b0dbc8d3b700fa15927150828e345]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626

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' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=258923&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=258923&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=258923&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' @ jenkins.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5803234.92423e-06
20.1692921.43650.077597
3-0.022645-0.19210.424084
4-0.334884-2.84160.002917
5-0.557729-4.73255e-06
6-0.653629-5.54620
7-0.526616-4.46851.4e-05
8-0.269955-2.29060.012457
90.0043880.03720.4852
100.1702591.44470.076441
110.5059584.29322.7e-05
120.8235586.98810
130.4912064.1684.2e-05
140.1497161.27040.104019
15-0.009742-0.08270.467173
16-0.271984-2.30790.011942
17-0.452441-3.83910.000131
18-0.533287-4.52511.2e-05
19-0.427058-3.62370.000269
20-0.217796-1.84810.03435
21-0.009846-0.08350.466824
220.1307291.10930.135501
230.3909473.31730.000714
240.6494995.51120
250.4077613.460.000456
260.116830.99130.162422
27-0.003018-0.02560.489821
28-0.199177-1.69010.04767
29-0.35361-3.00050.001851
30-0.413491-3.50860.00039
31-0.333684-2.83140.003002
32-0.17491-1.48420.071065
33-0.009183-0.07790.469055
340.1013170.85970.196404
350.2823852.39610.009585
360.4935884.18823.9e-05

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.580323 & 4.9242 & 3e-06 \tabularnewline
2 & 0.169292 & 1.4365 & 0.077597 \tabularnewline
3 & -0.022645 & -0.1921 & 0.424084 \tabularnewline
4 & -0.334884 & -2.8416 & 0.002917 \tabularnewline
5 & -0.557729 & -4.7325 & 5e-06 \tabularnewline
6 & -0.653629 & -5.5462 & 0 \tabularnewline
7 & -0.526616 & -4.4685 & 1.4e-05 \tabularnewline
8 & -0.269955 & -2.2906 & 0.012457 \tabularnewline
9 & 0.004388 & 0.0372 & 0.4852 \tabularnewline
10 & 0.170259 & 1.4447 & 0.076441 \tabularnewline
11 & 0.505958 & 4.2932 & 2.7e-05 \tabularnewline
12 & 0.823558 & 6.9881 & 0 \tabularnewline
13 & 0.491206 & 4.168 & 4.2e-05 \tabularnewline
14 & 0.149716 & 1.2704 & 0.104019 \tabularnewline
15 & -0.009742 & -0.0827 & 0.467173 \tabularnewline
16 & -0.271984 & -2.3079 & 0.011942 \tabularnewline
17 & -0.452441 & -3.8391 & 0.000131 \tabularnewline
18 & -0.533287 & -4.5251 & 1.2e-05 \tabularnewline
19 & -0.427058 & -3.6237 & 0.000269 \tabularnewline
20 & -0.217796 & -1.8481 & 0.03435 \tabularnewline
21 & -0.009846 & -0.0835 & 0.466824 \tabularnewline
22 & 0.130729 & 1.1093 & 0.135501 \tabularnewline
23 & 0.390947 & 3.3173 & 0.000714 \tabularnewline
24 & 0.649499 & 5.5112 & 0 \tabularnewline
25 & 0.407761 & 3.46 & 0.000456 \tabularnewline
26 & 0.11683 & 0.9913 & 0.162422 \tabularnewline
27 & -0.003018 & -0.0256 & 0.489821 \tabularnewline
28 & -0.199177 & -1.6901 & 0.04767 \tabularnewline
29 & -0.35361 & -3.0005 & 0.001851 \tabularnewline
30 & -0.413491 & -3.5086 & 0.00039 \tabularnewline
31 & -0.333684 & -2.8314 & 0.003002 \tabularnewline
32 & -0.17491 & -1.4842 & 0.071065 \tabularnewline
33 & -0.009183 & -0.0779 & 0.469055 \tabularnewline
34 & 0.101317 & 0.8597 & 0.196404 \tabularnewline
35 & 0.282385 & 2.3961 & 0.009585 \tabularnewline
36 & 0.493588 & 4.1882 & 3.9e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=258923&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]0.580323[/C][C]4.9242[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]0.169292[/C][C]1.4365[/C][C]0.077597[/C][/ROW]
[ROW][C]3[/C][C]-0.022645[/C][C]-0.1921[/C][C]0.424084[/C][/ROW]
[ROW][C]4[/C][C]-0.334884[/C][C]-2.8416[/C][C]0.002917[/C][/ROW]
[ROW][C]5[/C][C]-0.557729[/C][C]-4.7325[/C][C]5e-06[/C][/ROW]
[ROW][C]6[/C][C]-0.653629[/C][C]-5.5462[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.526616[/C][C]-4.4685[/C][C]1.4e-05[/C][/ROW]
[ROW][C]8[/C][C]-0.269955[/C][C]-2.2906[/C][C]0.012457[/C][/ROW]
[ROW][C]9[/C][C]0.004388[/C][C]0.0372[/C][C]0.4852[/C][/ROW]
[ROW][C]10[/C][C]0.170259[/C][C]1.4447[/C][C]0.076441[/C][/ROW]
[ROW][C]11[/C][C]0.505958[/C][C]4.2932[/C][C]2.7e-05[/C][/ROW]
[ROW][C]12[/C][C]0.823558[/C][C]6.9881[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.491206[/C][C]4.168[/C][C]4.2e-05[/C][/ROW]
[ROW][C]14[/C][C]0.149716[/C][C]1.2704[/C][C]0.104019[/C][/ROW]
[ROW][C]15[/C][C]-0.009742[/C][C]-0.0827[/C][C]0.467173[/C][/ROW]
[ROW][C]16[/C][C]-0.271984[/C][C]-2.3079[/C][C]0.011942[/C][/ROW]
[ROW][C]17[/C][C]-0.452441[/C][C]-3.8391[/C][C]0.000131[/C][/ROW]
[ROW][C]18[/C][C]-0.533287[/C][C]-4.5251[/C][C]1.2e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.427058[/C][C]-3.6237[/C][C]0.000269[/C][/ROW]
[ROW][C]20[/C][C]-0.217796[/C][C]-1.8481[/C][C]0.03435[/C][/ROW]
[ROW][C]21[/C][C]-0.009846[/C][C]-0.0835[/C][C]0.466824[/C][/ROW]
[ROW][C]22[/C][C]0.130729[/C][C]1.1093[/C][C]0.135501[/C][/ROW]
[ROW][C]23[/C][C]0.390947[/C][C]3.3173[/C][C]0.000714[/C][/ROW]
[ROW][C]24[/C][C]0.649499[/C][C]5.5112[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.407761[/C][C]3.46[/C][C]0.000456[/C][/ROW]
[ROW][C]26[/C][C]0.11683[/C][C]0.9913[/C][C]0.162422[/C][/ROW]
[ROW][C]27[/C][C]-0.003018[/C][C]-0.0256[/C][C]0.489821[/C][/ROW]
[ROW][C]28[/C][C]-0.199177[/C][C]-1.6901[/C][C]0.04767[/C][/ROW]
[ROW][C]29[/C][C]-0.35361[/C][C]-3.0005[/C][C]0.001851[/C][/ROW]
[ROW][C]30[/C][C]-0.413491[/C][C]-3.5086[/C][C]0.00039[/C][/ROW]
[ROW][C]31[/C][C]-0.333684[/C][C]-2.8314[/C][C]0.003002[/C][/ROW]
[ROW][C]32[/C][C]-0.17491[/C][C]-1.4842[/C][C]0.071065[/C][/ROW]
[ROW][C]33[/C][C]-0.009183[/C][C]-0.0779[/C][C]0.469055[/C][/ROW]
[ROW][C]34[/C][C]0.101317[/C][C]0.8597[/C][C]0.196404[/C][/ROW]
[ROW][C]35[/C][C]0.282385[/C][C]2.3961[/C][C]0.009585[/C][/ROW]
[ROW][C]36[/C][C]0.493588[/C][C]4.1882[/C][C]3.9e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=258923&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=258923&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
10.5803234.92423e-06
20.1692921.43650.077597
3-0.022645-0.19210.424084
4-0.334884-2.84160.002917
5-0.557729-4.73255e-06
6-0.653629-5.54620
7-0.526616-4.46851.4e-05
8-0.269955-2.29060.012457
90.0043880.03720.4852
100.1702591.44470.076441
110.5059584.29322.7e-05
120.8235586.98810
130.4912064.1684.2e-05
140.1497161.27040.104019
15-0.009742-0.08270.467173
16-0.271984-2.30790.011942
17-0.452441-3.83910.000131
18-0.533287-4.52511.2e-05
19-0.427058-3.62370.000269
20-0.217796-1.84810.03435
21-0.009846-0.08350.466824
220.1307291.10930.135501
230.3909473.31730.000714
240.6494995.51120
250.4077613.460.000456
260.116830.99130.162422
27-0.003018-0.02560.489821
28-0.199177-1.69010.04767
29-0.35361-3.00050.001851
30-0.413491-3.50860.00039
31-0.333684-2.83140.003002
32-0.17491-1.48420.071065
33-0.009183-0.07790.469055
340.1013170.85970.196404
350.2823852.39610.009585
360.4935884.18823.9e-05






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5803234.92423e-06
2-0.252529-2.14280.017756
30.001370.01160.49538
4-0.444964-3.77560.000163
5-0.239114-2.02890.023081
6-0.455135-3.86190.000122
7-0.155908-1.32290.095024
8-0.296482-2.51570.007055
9-0.137955-1.17060.122813
10-0.570015-4.83674e-06
110.2425912.05850.021583
120.2444862.07450.020803
13-0.384684-3.26420.000841
14-0.140458-1.19180.118622
15-0.111465-0.94580.173704
16-0.001189-0.01010.49599
170.0018820.0160.493652
180.0133290.11310.455132
190.0106440.09030.464142
20-0.109556-0.92960.177839
210.0173480.14720.441691
22-0.002071-0.01760.493013
23-0.029062-0.24660.40296
240.0292940.24860.402201
250.0163750.13890.44494
26-0.110983-0.94170.174743
270.0074310.06310.474948
280.0078010.06620.473705
29-0.017509-0.14860.441153
300.0219140.18590.426504
31-0.026431-0.22430.41159
32-0.01444-0.12250.451411
330.0378320.3210.374565
340.0275650.23390.407864
35-0.046318-0.3930.347731
360.0016120.01370.494563

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.580323 & 4.9242 & 3e-06 \tabularnewline
2 & -0.252529 & -2.1428 & 0.017756 \tabularnewline
3 & 0.00137 & 0.0116 & 0.49538 \tabularnewline
4 & -0.444964 & -3.7756 & 0.000163 \tabularnewline
5 & -0.239114 & -2.0289 & 0.023081 \tabularnewline
6 & -0.455135 & -3.8619 & 0.000122 \tabularnewline
7 & -0.155908 & -1.3229 & 0.095024 \tabularnewline
8 & -0.296482 & -2.5157 & 0.007055 \tabularnewline
9 & -0.137955 & -1.1706 & 0.122813 \tabularnewline
10 & -0.570015 & -4.8367 & 4e-06 \tabularnewline
11 & 0.242591 & 2.0585 & 0.021583 \tabularnewline
12 & 0.244486 & 2.0745 & 0.020803 \tabularnewline
13 & -0.384684 & -3.2642 & 0.000841 \tabularnewline
14 & -0.140458 & -1.1918 & 0.118622 \tabularnewline
15 & -0.111465 & -0.9458 & 0.173704 \tabularnewline
16 & -0.001189 & -0.0101 & 0.49599 \tabularnewline
17 & 0.001882 & 0.016 & 0.493652 \tabularnewline
18 & 0.013329 & 0.1131 & 0.455132 \tabularnewline
19 & 0.010644 & 0.0903 & 0.464142 \tabularnewline
20 & -0.109556 & -0.9296 & 0.177839 \tabularnewline
21 & 0.017348 & 0.1472 & 0.441691 \tabularnewline
22 & -0.002071 & -0.0176 & 0.493013 \tabularnewline
23 & -0.029062 & -0.2466 & 0.40296 \tabularnewline
24 & 0.029294 & 0.2486 & 0.402201 \tabularnewline
25 & 0.016375 & 0.1389 & 0.44494 \tabularnewline
26 & -0.110983 & -0.9417 & 0.174743 \tabularnewline
27 & 0.007431 & 0.0631 & 0.474948 \tabularnewline
28 & 0.007801 & 0.0662 & 0.473705 \tabularnewline
29 & -0.017509 & -0.1486 & 0.441153 \tabularnewline
30 & 0.021914 & 0.1859 & 0.426504 \tabularnewline
31 & -0.026431 & -0.2243 & 0.41159 \tabularnewline
32 & -0.01444 & -0.1225 & 0.451411 \tabularnewline
33 & 0.037832 & 0.321 & 0.374565 \tabularnewline
34 & 0.027565 & 0.2339 & 0.407864 \tabularnewline
35 & -0.046318 & -0.393 & 0.347731 \tabularnewline
36 & 0.001612 & 0.0137 & 0.494563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=258923&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]0.580323[/C][C]4.9242[/C][C]3e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.252529[/C][C]-2.1428[/C][C]0.017756[/C][/ROW]
[ROW][C]3[/C][C]0.00137[/C][C]0.0116[/C][C]0.49538[/C][/ROW]
[ROW][C]4[/C][C]-0.444964[/C][C]-3.7756[/C][C]0.000163[/C][/ROW]
[ROW][C]5[/C][C]-0.239114[/C][C]-2.0289[/C][C]0.023081[/C][/ROW]
[ROW][C]6[/C][C]-0.455135[/C][C]-3.8619[/C][C]0.000122[/C][/ROW]
[ROW][C]7[/C][C]-0.155908[/C][C]-1.3229[/C][C]0.095024[/C][/ROW]
[ROW][C]8[/C][C]-0.296482[/C][C]-2.5157[/C][C]0.007055[/C][/ROW]
[ROW][C]9[/C][C]-0.137955[/C][C]-1.1706[/C][C]0.122813[/C][/ROW]
[ROW][C]10[/C][C]-0.570015[/C][C]-4.8367[/C][C]4e-06[/C][/ROW]
[ROW][C]11[/C][C]0.242591[/C][C]2.0585[/C][C]0.021583[/C][/ROW]
[ROW][C]12[/C][C]0.244486[/C][C]2.0745[/C][C]0.020803[/C][/ROW]
[ROW][C]13[/C][C]-0.384684[/C][C]-3.2642[/C][C]0.000841[/C][/ROW]
[ROW][C]14[/C][C]-0.140458[/C][C]-1.1918[/C][C]0.118622[/C][/ROW]
[ROW][C]15[/C][C]-0.111465[/C][C]-0.9458[/C][C]0.173704[/C][/ROW]
[ROW][C]16[/C][C]-0.001189[/C][C]-0.0101[/C][C]0.49599[/C][/ROW]
[ROW][C]17[/C][C]0.001882[/C][C]0.016[/C][C]0.493652[/C][/ROW]
[ROW][C]18[/C][C]0.013329[/C][C]0.1131[/C][C]0.455132[/C][/ROW]
[ROW][C]19[/C][C]0.010644[/C][C]0.0903[/C][C]0.464142[/C][/ROW]
[ROW][C]20[/C][C]-0.109556[/C][C]-0.9296[/C][C]0.177839[/C][/ROW]
[ROW][C]21[/C][C]0.017348[/C][C]0.1472[/C][C]0.441691[/C][/ROW]
[ROW][C]22[/C][C]-0.002071[/C][C]-0.0176[/C][C]0.493013[/C][/ROW]
[ROW][C]23[/C][C]-0.029062[/C][C]-0.2466[/C][C]0.40296[/C][/ROW]
[ROW][C]24[/C][C]0.029294[/C][C]0.2486[/C][C]0.402201[/C][/ROW]
[ROW][C]25[/C][C]0.016375[/C][C]0.1389[/C][C]0.44494[/C][/ROW]
[ROW][C]26[/C][C]-0.110983[/C][C]-0.9417[/C][C]0.174743[/C][/ROW]
[ROW][C]27[/C][C]0.007431[/C][C]0.0631[/C][C]0.474948[/C][/ROW]
[ROW][C]28[/C][C]0.007801[/C][C]0.0662[/C][C]0.473705[/C][/ROW]
[ROW][C]29[/C][C]-0.017509[/C][C]-0.1486[/C][C]0.441153[/C][/ROW]
[ROW][C]30[/C][C]0.021914[/C][C]0.1859[/C][C]0.426504[/C][/ROW]
[ROW][C]31[/C][C]-0.026431[/C][C]-0.2243[/C][C]0.41159[/C][/ROW]
[ROW][C]32[/C][C]-0.01444[/C][C]-0.1225[/C][C]0.451411[/C][/ROW]
[ROW][C]33[/C][C]0.037832[/C][C]0.321[/C][C]0.374565[/C][/ROW]
[ROW][C]34[/C][C]0.027565[/C][C]0.2339[/C][C]0.407864[/C][/ROW]
[ROW][C]35[/C][C]-0.046318[/C][C]-0.393[/C][C]0.347731[/C][/ROW]
[ROW][C]36[/C][C]0.001612[/C][C]0.0137[/C][C]0.494563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=258923&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=258923&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
10.5803234.92423e-06
2-0.252529-2.14280.017756
30.001370.01160.49538
4-0.444964-3.77560.000163
5-0.239114-2.02890.023081
6-0.455135-3.86190.000122
7-0.155908-1.32290.095024
8-0.296482-2.51570.007055
9-0.137955-1.17060.122813
10-0.570015-4.83674e-06
110.2425912.05850.021583
120.2444862.07450.020803
13-0.384684-3.26420.000841
14-0.140458-1.19180.118622
15-0.111465-0.94580.173704
16-0.001189-0.01010.49599
170.0018820.0160.493652
180.0133290.11310.455132
190.0106440.09030.464142
20-0.109556-0.92960.177839
210.0173480.14720.441691
22-0.002071-0.01760.493013
23-0.029062-0.24660.40296
240.0292940.24860.402201
250.0163750.13890.44494
26-0.110983-0.94170.174743
270.0074310.06310.474948
280.0078010.06620.473705
29-0.017509-0.14860.441153
300.0219140.18590.426504
31-0.026431-0.22430.41159
32-0.01444-0.12250.451411
330.0378320.3210.374565
340.0275650.23390.407864
35-0.046318-0.3930.347731
360.0016120.01370.494563


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')