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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 computationFri, 27 Nov 2009 02:24:36 -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/t12593139503a3ocb9gju99ls0.htm/, Retrieved Sun, 28 Apr 2024 22:06:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60494, Retrieved Sun, 28 Apr 2024 22:06:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
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 12:26:39] [b98453cac15ba1066b407e146608df68]
- R PD          [(Partial) Autocorrelation Function] [Workshop8 ACF d=2...] [2009-11-27 09:24:36] [5ed0eef5d4509bbfdac0ae6d87f3b4bf] [Current]
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Dataseries X:
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523




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=60494&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=60494&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60494&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
1-0.574363-4.25964e-05
20.0408460.30290.381547
30.0975670.72360.236197
40.0028770.02130.491527
5-0.102179-0.75780.225908
60.1134950.84170.2018
7-0.145589-1.07970.14249
80.1261350.93540.176825
90.0144960.10750.457389
10-0.296027-2.19540.016186
110.4366443.23820.001021
12-0.235096-1.74350.043415
13-0.090754-0.6730.251868
140.1832891.35930.089799
15-0.050193-0.37220.355572
16-0.048666-0.36090.359773
170.1156140.85740.197467
18-0.162466-1.20490.116705
190.1250770.92760.178835
200.0329580.24440.403907
21-0.173171-1.28430.102215
220.1316660.97650.166556
230.0194420.14420.442939
24-0.116614-0.86480.195444
250.1012420.75080.227978
26-0.039265-0.29120.385999
27-0.018164-0.13470.446666
28-0.023181-0.17190.432068
290.0300620.22290.412203
30-0.054581-0.40480.343603
310.1376681.0210.155868
32-0.172225-1.27730.103438
330.1222710.90680.184238
34-0.051667-0.38320.351536
350.0513980.38120.352269
36-0.027614-0.20480.419245

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.574363 & -4.2596 & 4e-05 \tabularnewline
2 & 0.040846 & 0.3029 & 0.381547 \tabularnewline
3 & 0.097567 & 0.7236 & 0.236197 \tabularnewline
4 & 0.002877 & 0.0213 & 0.491527 \tabularnewline
5 & -0.102179 & -0.7578 & 0.225908 \tabularnewline
6 & 0.113495 & 0.8417 & 0.2018 \tabularnewline
7 & -0.145589 & -1.0797 & 0.14249 \tabularnewline
8 & 0.126135 & 0.9354 & 0.176825 \tabularnewline
9 & 0.014496 & 0.1075 & 0.457389 \tabularnewline
10 & -0.296027 & -2.1954 & 0.016186 \tabularnewline
11 & 0.436644 & 3.2382 & 0.001021 \tabularnewline
12 & -0.235096 & -1.7435 & 0.043415 \tabularnewline
13 & -0.090754 & -0.673 & 0.251868 \tabularnewline
14 & 0.183289 & 1.3593 & 0.089799 \tabularnewline
15 & -0.050193 & -0.3722 & 0.355572 \tabularnewline
16 & -0.048666 & -0.3609 & 0.359773 \tabularnewline
17 & 0.115614 & 0.8574 & 0.197467 \tabularnewline
18 & -0.162466 & -1.2049 & 0.116705 \tabularnewline
19 & 0.125077 & 0.9276 & 0.178835 \tabularnewline
20 & 0.032958 & 0.2444 & 0.403907 \tabularnewline
21 & -0.173171 & -1.2843 & 0.102215 \tabularnewline
22 & 0.131666 & 0.9765 & 0.166556 \tabularnewline
23 & 0.019442 & 0.1442 & 0.442939 \tabularnewline
24 & -0.116614 & -0.8648 & 0.195444 \tabularnewline
25 & 0.101242 & 0.7508 & 0.227978 \tabularnewline
26 & -0.039265 & -0.2912 & 0.385999 \tabularnewline
27 & -0.018164 & -0.1347 & 0.446666 \tabularnewline
28 & -0.023181 & -0.1719 & 0.432068 \tabularnewline
29 & 0.030062 & 0.2229 & 0.412203 \tabularnewline
30 & -0.054581 & -0.4048 & 0.343603 \tabularnewline
31 & 0.137668 & 1.021 & 0.155868 \tabularnewline
32 & -0.172225 & -1.2773 & 0.103438 \tabularnewline
33 & 0.122271 & 0.9068 & 0.184238 \tabularnewline
34 & -0.051667 & -0.3832 & 0.351536 \tabularnewline
35 & 0.051398 & 0.3812 & 0.352269 \tabularnewline
36 & -0.027614 & -0.2048 & 0.419245 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60494&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]-0.574363[/C][C]-4.2596[/C][C]4e-05[/C][/ROW]
[ROW][C]2[/C][C]0.040846[/C][C]0.3029[/C][C]0.381547[/C][/ROW]
[ROW][C]3[/C][C]0.097567[/C][C]0.7236[/C][C]0.236197[/C][/ROW]
[ROW][C]4[/C][C]0.002877[/C][C]0.0213[/C][C]0.491527[/C][/ROW]
[ROW][C]5[/C][C]-0.102179[/C][C]-0.7578[/C][C]0.225908[/C][/ROW]
[ROW][C]6[/C][C]0.113495[/C][C]0.8417[/C][C]0.2018[/C][/ROW]
[ROW][C]7[/C][C]-0.145589[/C][C]-1.0797[/C][C]0.14249[/C][/ROW]
[ROW][C]8[/C][C]0.126135[/C][C]0.9354[/C][C]0.176825[/C][/ROW]
[ROW][C]9[/C][C]0.014496[/C][C]0.1075[/C][C]0.457389[/C][/ROW]
[ROW][C]10[/C][C]-0.296027[/C][C]-2.1954[/C][C]0.016186[/C][/ROW]
[ROW][C]11[/C][C]0.436644[/C][C]3.2382[/C][C]0.001021[/C][/ROW]
[ROW][C]12[/C][C]-0.235096[/C][C]-1.7435[/C][C]0.043415[/C][/ROW]
[ROW][C]13[/C][C]-0.090754[/C][C]-0.673[/C][C]0.251868[/C][/ROW]
[ROW][C]14[/C][C]0.183289[/C][C]1.3593[/C][C]0.089799[/C][/ROW]
[ROW][C]15[/C][C]-0.050193[/C][C]-0.3722[/C][C]0.355572[/C][/ROW]
[ROW][C]16[/C][C]-0.048666[/C][C]-0.3609[/C][C]0.359773[/C][/ROW]
[ROW][C]17[/C][C]0.115614[/C][C]0.8574[/C][C]0.197467[/C][/ROW]
[ROW][C]18[/C][C]-0.162466[/C][C]-1.2049[/C][C]0.116705[/C][/ROW]
[ROW][C]19[/C][C]0.125077[/C][C]0.9276[/C][C]0.178835[/C][/ROW]
[ROW][C]20[/C][C]0.032958[/C][C]0.2444[/C][C]0.403907[/C][/ROW]
[ROW][C]21[/C][C]-0.173171[/C][C]-1.2843[/C][C]0.102215[/C][/ROW]
[ROW][C]22[/C][C]0.131666[/C][C]0.9765[/C][C]0.166556[/C][/ROW]
[ROW][C]23[/C][C]0.019442[/C][C]0.1442[/C][C]0.442939[/C][/ROW]
[ROW][C]24[/C][C]-0.116614[/C][C]-0.8648[/C][C]0.195444[/C][/ROW]
[ROW][C]25[/C][C]0.101242[/C][C]0.7508[/C][C]0.227978[/C][/ROW]
[ROW][C]26[/C][C]-0.039265[/C][C]-0.2912[/C][C]0.385999[/C][/ROW]
[ROW][C]27[/C][C]-0.018164[/C][C]-0.1347[/C][C]0.446666[/C][/ROW]
[ROW][C]28[/C][C]-0.023181[/C][C]-0.1719[/C][C]0.432068[/C][/ROW]
[ROW][C]29[/C][C]0.030062[/C][C]0.2229[/C][C]0.412203[/C][/ROW]
[ROW][C]30[/C][C]-0.054581[/C][C]-0.4048[/C][C]0.343603[/C][/ROW]
[ROW][C]31[/C][C]0.137668[/C][C]1.021[/C][C]0.155868[/C][/ROW]
[ROW][C]32[/C][C]-0.172225[/C][C]-1.2773[/C][C]0.103438[/C][/ROW]
[ROW][C]33[/C][C]0.122271[/C][C]0.9068[/C][C]0.184238[/C][/ROW]
[ROW][C]34[/C][C]-0.051667[/C][C]-0.3832[/C][C]0.351536[/C][/ROW]
[ROW][C]35[/C][C]0.051398[/C][C]0.3812[/C][C]0.352269[/C][/ROW]
[ROW][C]36[/C][C]-0.027614[/C][C]-0.2048[/C][C]0.419245[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60494&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60494&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
1-0.574363-4.25964e-05
20.0408460.30290.381547
30.0975670.72360.236197
40.0028770.02130.491527
5-0.102179-0.75780.225908
60.1134950.84170.2018
7-0.145589-1.07970.14249
80.1261350.93540.176825
90.0144960.10750.457389
10-0.296027-2.19540.016186
110.4366443.23820.001021
12-0.235096-1.74350.043415
13-0.090754-0.6730.251868
140.1832891.35930.089799
15-0.050193-0.37220.355572
16-0.048666-0.36090.359773
170.1156140.85740.197467
18-0.162466-1.20490.116705
190.1250770.92760.178835
200.0329580.24440.403907
21-0.173171-1.28430.102215
220.1316660.97650.166556
230.0194420.14420.442939
24-0.116614-0.86480.195444
250.1012420.75080.227978
26-0.039265-0.29120.385999
27-0.018164-0.13470.446666
28-0.023181-0.17190.432068
290.0300620.22290.412203
30-0.054581-0.40480.343603
310.1376681.0210.155868
32-0.172225-1.27730.103438
330.1222710.90680.184238
34-0.051667-0.38320.351536
350.0513980.38120.352269
36-0.027614-0.20480.419245







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.574363-4.25964e-05
2-0.431345-3.19890.001145
3-0.213781-1.58540.0593
4-0.011346-0.08410.466624
5-0.071091-0.52720.300079
60.0192620.14290.443464
7-0.165255-1.22560.112792
8-0.071999-0.5340.29776
90.0867460.64330.261344
10-0.365191-2.70830.004497
110.0732620.54330.294551
120.0455480.33780.368403
13-0.152624-1.13190.131296
14-0.038617-0.28640.387828
15-0.072698-0.53910.295983
160.0418950.31070.378602
170.0960910.71260.239544
18-0.048046-0.35630.361483
190.0020470.01520.493971
200.0264430.19610.422624
210.0734970.54510.293954
22-0.084897-0.62960.265778
23-0.028124-0.20860.417775
240.0837840.62140.268466
250.0114780.08510.466236
26-0.004042-0.030.488098
27-0.004247-0.03150.487492
28-0.228693-1.6960.047767
29-0.040435-0.29990.382702
30-0.167096-1.23920.110263
31-0.055329-0.41030.341579
32-0.062697-0.4650.321892
33-0.008626-0.0640.474611
34-0.124682-0.92470.179589
35-0.044677-0.33130.370826
360.0516910.38330.351469

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.574363 & -4.2596 & 4e-05 \tabularnewline
2 & -0.431345 & -3.1989 & 0.001145 \tabularnewline
3 & -0.213781 & -1.5854 & 0.0593 \tabularnewline
4 & -0.011346 & -0.0841 & 0.466624 \tabularnewline
5 & -0.071091 & -0.5272 & 0.300079 \tabularnewline
6 & 0.019262 & 0.1429 & 0.443464 \tabularnewline
7 & -0.165255 & -1.2256 & 0.112792 \tabularnewline
8 & -0.071999 & -0.534 & 0.29776 \tabularnewline
9 & 0.086746 & 0.6433 & 0.261344 \tabularnewline
10 & -0.365191 & -2.7083 & 0.004497 \tabularnewline
11 & 0.073262 & 0.5433 & 0.294551 \tabularnewline
12 & 0.045548 & 0.3378 & 0.368403 \tabularnewline
13 & -0.152624 & -1.1319 & 0.131296 \tabularnewline
14 & -0.038617 & -0.2864 & 0.387828 \tabularnewline
15 & -0.072698 & -0.5391 & 0.295983 \tabularnewline
16 & 0.041895 & 0.3107 & 0.378602 \tabularnewline
17 & 0.096091 & 0.7126 & 0.239544 \tabularnewline
18 & -0.048046 & -0.3563 & 0.361483 \tabularnewline
19 & 0.002047 & 0.0152 & 0.493971 \tabularnewline
20 & 0.026443 & 0.1961 & 0.422624 \tabularnewline
21 & 0.073497 & 0.5451 & 0.293954 \tabularnewline
22 & -0.084897 & -0.6296 & 0.265778 \tabularnewline
23 & -0.028124 & -0.2086 & 0.417775 \tabularnewline
24 & 0.083784 & 0.6214 & 0.268466 \tabularnewline
25 & 0.011478 & 0.0851 & 0.466236 \tabularnewline
26 & -0.004042 & -0.03 & 0.488098 \tabularnewline
27 & -0.004247 & -0.0315 & 0.487492 \tabularnewline
28 & -0.228693 & -1.696 & 0.047767 \tabularnewline
29 & -0.040435 & -0.2999 & 0.382702 \tabularnewline
30 & -0.167096 & -1.2392 & 0.110263 \tabularnewline
31 & -0.055329 & -0.4103 & 0.341579 \tabularnewline
32 & -0.062697 & -0.465 & 0.321892 \tabularnewline
33 & -0.008626 & -0.064 & 0.474611 \tabularnewline
34 & -0.124682 & -0.9247 & 0.179589 \tabularnewline
35 & -0.044677 & -0.3313 & 0.370826 \tabularnewline
36 & 0.051691 & 0.3833 & 0.351469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60494&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]-0.574363[/C][C]-4.2596[/C][C]4e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.431345[/C][C]-3.1989[/C][C]0.001145[/C][/ROW]
[ROW][C]3[/C][C]-0.213781[/C][C]-1.5854[/C][C]0.0593[/C][/ROW]
[ROW][C]4[/C][C]-0.011346[/C][C]-0.0841[/C][C]0.466624[/C][/ROW]
[ROW][C]5[/C][C]-0.071091[/C][C]-0.5272[/C][C]0.300079[/C][/ROW]
[ROW][C]6[/C][C]0.019262[/C][C]0.1429[/C][C]0.443464[/C][/ROW]
[ROW][C]7[/C][C]-0.165255[/C][C]-1.2256[/C][C]0.112792[/C][/ROW]
[ROW][C]8[/C][C]-0.071999[/C][C]-0.534[/C][C]0.29776[/C][/ROW]
[ROW][C]9[/C][C]0.086746[/C][C]0.6433[/C][C]0.261344[/C][/ROW]
[ROW][C]10[/C][C]-0.365191[/C][C]-2.7083[/C][C]0.004497[/C][/ROW]
[ROW][C]11[/C][C]0.073262[/C][C]0.5433[/C][C]0.294551[/C][/ROW]
[ROW][C]12[/C][C]0.045548[/C][C]0.3378[/C][C]0.368403[/C][/ROW]
[ROW][C]13[/C][C]-0.152624[/C][C]-1.1319[/C][C]0.131296[/C][/ROW]
[ROW][C]14[/C][C]-0.038617[/C][C]-0.2864[/C][C]0.387828[/C][/ROW]
[ROW][C]15[/C][C]-0.072698[/C][C]-0.5391[/C][C]0.295983[/C][/ROW]
[ROW][C]16[/C][C]0.041895[/C][C]0.3107[/C][C]0.378602[/C][/ROW]
[ROW][C]17[/C][C]0.096091[/C][C]0.7126[/C][C]0.239544[/C][/ROW]
[ROW][C]18[/C][C]-0.048046[/C][C]-0.3563[/C][C]0.361483[/C][/ROW]
[ROW][C]19[/C][C]0.002047[/C][C]0.0152[/C][C]0.493971[/C][/ROW]
[ROW][C]20[/C][C]0.026443[/C][C]0.1961[/C][C]0.422624[/C][/ROW]
[ROW][C]21[/C][C]0.073497[/C][C]0.5451[/C][C]0.293954[/C][/ROW]
[ROW][C]22[/C][C]-0.084897[/C][C]-0.6296[/C][C]0.265778[/C][/ROW]
[ROW][C]23[/C][C]-0.028124[/C][C]-0.2086[/C][C]0.417775[/C][/ROW]
[ROW][C]24[/C][C]0.083784[/C][C]0.6214[/C][C]0.268466[/C][/ROW]
[ROW][C]25[/C][C]0.011478[/C][C]0.0851[/C][C]0.466236[/C][/ROW]
[ROW][C]26[/C][C]-0.004042[/C][C]-0.03[/C][C]0.488098[/C][/ROW]
[ROW][C]27[/C][C]-0.004247[/C][C]-0.0315[/C][C]0.487492[/C][/ROW]
[ROW][C]28[/C][C]-0.228693[/C][C]-1.696[/C][C]0.047767[/C][/ROW]
[ROW][C]29[/C][C]-0.040435[/C][C]-0.2999[/C][C]0.382702[/C][/ROW]
[ROW][C]30[/C][C]-0.167096[/C][C]-1.2392[/C][C]0.110263[/C][/ROW]
[ROW][C]31[/C][C]-0.055329[/C][C]-0.4103[/C][C]0.341579[/C][/ROW]
[ROW][C]32[/C][C]-0.062697[/C][C]-0.465[/C][C]0.321892[/C][/ROW]
[ROW][C]33[/C][C]-0.008626[/C][C]-0.064[/C][C]0.474611[/C][/ROW]
[ROW][C]34[/C][C]-0.124682[/C][C]-0.9247[/C][C]0.179589[/C][/ROW]
[ROW][C]35[/C][C]-0.044677[/C][C]-0.3313[/C][C]0.370826[/C][/ROW]
[ROW][C]36[/C][C]0.051691[/C][C]0.3833[/C][C]0.351469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60494&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60494&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
1-0.574363-4.25964e-05
2-0.431345-3.19890.001145
3-0.213781-1.58540.0593
4-0.011346-0.08410.466624
5-0.071091-0.52720.300079
60.0192620.14290.443464
7-0.165255-1.22560.112792
8-0.071999-0.5340.29776
90.0867460.64330.261344
10-0.365191-2.70830.004497
110.0732620.54330.294551
120.0455480.33780.368403
13-0.152624-1.13190.131296
14-0.038617-0.28640.387828
15-0.072698-0.53910.295983
160.0418950.31070.378602
170.0960910.71260.239544
18-0.048046-0.35630.361483
190.0020470.01520.493971
200.0264430.19610.422624
210.0734970.54510.293954
22-0.084897-0.62960.265778
23-0.028124-0.20860.417775
240.0837840.62140.268466
250.0114780.08510.466236
26-0.004042-0.030.488098
27-0.004247-0.03150.487492
28-0.228693-1.6960.047767
29-0.040435-0.29990.382702
30-0.167096-1.23920.110263
31-0.055329-0.41030.341579
32-0.062697-0.4650.321892
33-0.008626-0.0640.474611
34-0.124682-0.92470.179589
35-0.044677-0.33130.370826
360.0516910.38330.351469



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')