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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 computationMon, 30 Nov 2009 11:45:37 -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/30/t12596067692ht8kx6r7w1chqr.htm/, Retrieved Wed, 01 May 2024 14:25:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61853, Retrieved Wed, 01 May 2024 14:25:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

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]
-   PD        [(Partial) Autocorrelation Function] [ACF (d=0, D=1)] [2009-11-27 10:14:21] [f7fc9270f813d017f9fa5b506fdc7682]
-   P             [(Partial) Autocorrelation Function] [WS8 d = 2] [2009-11-30 18:45:37] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
593530
610943
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

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=61853&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=61853&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61853&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
1-0.165425-1.2920.100613
2-0.282957-2.210.015435
3-0.095692-0.74740.228853
4-0.119485-0.93320.177196
50.0883640.69010.24636
60.1758091.37310.087372
70.1181690.92290.17984
8-0.164894-1.28790.101329
9-0.074602-0.58270.281136
10-0.2993-2.33760.011352
11-0.002969-0.02320.490788
120.7288455.69250
13-0.146753-1.14620.1281
14-0.221654-1.73120.044238
15-0.071423-0.55780.289502
16-0.099748-0.77910.219479
170.077260.60340.274233
180.1309671.02290.155202
190.1079160.84290.201302
20-0.156461-1.2220.113205
21-0.075618-0.59060.278486
22-0.208468-1.62820.05432
230.0460640.35980.36013
240.5178054.04427.5e-05
25-0.103631-0.80940.210719
26-0.200681-1.56740.061101
27-0.026017-0.20320.419827
28-0.069278-0.54110.295213
290.0673070.52570.300506
300.0766810.59890.275729
310.0963980.75290.227206
32-0.146152-1.14150.129064
33-0.065712-0.51320.304824
34-0.103258-0.80650.211552
350.0544710.42540.33601
360.2940062.29630.012555

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.165425 & -1.292 & 0.100613 \tabularnewline
2 & -0.282957 & -2.21 & 0.015435 \tabularnewline
3 & -0.095692 & -0.7474 & 0.228853 \tabularnewline
4 & -0.119485 & -0.9332 & 0.177196 \tabularnewline
5 & 0.088364 & 0.6901 & 0.24636 \tabularnewline
6 & 0.175809 & 1.3731 & 0.087372 \tabularnewline
7 & 0.118169 & 0.9229 & 0.17984 \tabularnewline
8 & -0.164894 & -1.2879 & 0.101329 \tabularnewline
9 & -0.074602 & -0.5827 & 0.281136 \tabularnewline
10 & -0.2993 & -2.3376 & 0.011352 \tabularnewline
11 & -0.002969 & -0.0232 & 0.490788 \tabularnewline
12 & 0.728845 & 5.6925 & 0 \tabularnewline
13 & -0.146753 & -1.1462 & 0.1281 \tabularnewline
14 & -0.221654 & -1.7312 & 0.044238 \tabularnewline
15 & -0.071423 & -0.5578 & 0.289502 \tabularnewline
16 & -0.099748 & -0.7791 & 0.219479 \tabularnewline
17 & 0.07726 & 0.6034 & 0.274233 \tabularnewline
18 & 0.130967 & 1.0229 & 0.155202 \tabularnewline
19 & 0.107916 & 0.8429 & 0.201302 \tabularnewline
20 & -0.156461 & -1.222 & 0.113205 \tabularnewline
21 & -0.075618 & -0.5906 & 0.278486 \tabularnewline
22 & -0.208468 & -1.6282 & 0.05432 \tabularnewline
23 & 0.046064 & 0.3598 & 0.36013 \tabularnewline
24 & 0.517805 & 4.0442 & 7.5e-05 \tabularnewline
25 & -0.103631 & -0.8094 & 0.210719 \tabularnewline
26 & -0.200681 & -1.5674 & 0.061101 \tabularnewline
27 & -0.026017 & -0.2032 & 0.419827 \tabularnewline
28 & -0.069278 & -0.5411 & 0.295213 \tabularnewline
29 & 0.067307 & 0.5257 & 0.300506 \tabularnewline
30 & 0.076681 & 0.5989 & 0.275729 \tabularnewline
31 & 0.096398 & 0.7529 & 0.227206 \tabularnewline
32 & -0.146152 & -1.1415 & 0.129064 \tabularnewline
33 & -0.065712 & -0.5132 & 0.304824 \tabularnewline
34 & -0.103258 & -0.8065 & 0.211552 \tabularnewline
35 & 0.054471 & 0.4254 & 0.33601 \tabularnewline
36 & 0.294006 & 2.2963 & 0.012555 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61853&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]-0.165425[/C][C]-1.292[/C][C]0.100613[/C][/ROW]
[ROW][C]2[/C][C]-0.282957[/C][C]-2.21[/C][C]0.015435[/C][/ROW]
[ROW][C]3[/C][C]-0.095692[/C][C]-0.7474[/C][C]0.228853[/C][/ROW]
[ROW][C]4[/C][C]-0.119485[/C][C]-0.9332[/C][C]0.177196[/C][/ROW]
[ROW][C]5[/C][C]0.088364[/C][C]0.6901[/C][C]0.24636[/C][/ROW]
[ROW][C]6[/C][C]0.175809[/C][C]1.3731[/C][C]0.087372[/C][/ROW]
[ROW][C]7[/C][C]0.118169[/C][C]0.9229[/C][C]0.17984[/C][/ROW]
[ROW][C]8[/C][C]-0.164894[/C][C]-1.2879[/C][C]0.101329[/C][/ROW]
[ROW][C]9[/C][C]-0.074602[/C][C]-0.5827[/C][C]0.281136[/C][/ROW]
[ROW][C]10[/C][C]-0.2993[/C][C]-2.3376[/C][C]0.011352[/C][/ROW]
[ROW][C]11[/C][C]-0.002969[/C][C]-0.0232[/C][C]0.490788[/C][/ROW]
[ROW][C]12[/C][C]0.728845[/C][C]5.6925[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.146753[/C][C]-1.1462[/C][C]0.1281[/C][/ROW]
[ROW][C]14[/C][C]-0.221654[/C][C]-1.7312[/C][C]0.044238[/C][/ROW]
[ROW][C]15[/C][C]-0.071423[/C][C]-0.5578[/C][C]0.289502[/C][/ROW]
[ROW][C]16[/C][C]-0.099748[/C][C]-0.7791[/C][C]0.219479[/C][/ROW]
[ROW][C]17[/C][C]0.07726[/C][C]0.6034[/C][C]0.274233[/C][/ROW]
[ROW][C]18[/C][C]0.130967[/C][C]1.0229[/C][C]0.155202[/C][/ROW]
[ROW][C]19[/C][C]0.107916[/C][C]0.8429[/C][C]0.201302[/C][/ROW]
[ROW][C]20[/C][C]-0.156461[/C][C]-1.222[/C][C]0.113205[/C][/ROW]
[ROW][C]21[/C][C]-0.075618[/C][C]-0.5906[/C][C]0.278486[/C][/ROW]
[ROW][C]22[/C][C]-0.208468[/C][C]-1.6282[/C][C]0.05432[/C][/ROW]
[ROW][C]23[/C][C]0.046064[/C][C]0.3598[/C][C]0.36013[/C][/ROW]
[ROW][C]24[/C][C]0.517805[/C][C]4.0442[/C][C]7.5e-05[/C][/ROW]
[ROW][C]25[/C][C]-0.103631[/C][C]-0.8094[/C][C]0.210719[/C][/ROW]
[ROW][C]26[/C][C]-0.200681[/C][C]-1.5674[/C][C]0.061101[/C][/ROW]
[ROW][C]27[/C][C]-0.026017[/C][C]-0.2032[/C][C]0.419827[/C][/ROW]
[ROW][C]28[/C][C]-0.069278[/C][C]-0.5411[/C][C]0.295213[/C][/ROW]
[ROW][C]29[/C][C]0.067307[/C][C]0.5257[/C][C]0.300506[/C][/ROW]
[ROW][C]30[/C][C]0.076681[/C][C]0.5989[/C][C]0.275729[/C][/ROW]
[ROW][C]31[/C][C]0.096398[/C][C]0.7529[/C][C]0.227206[/C][/ROW]
[ROW][C]32[/C][C]-0.146152[/C][C]-1.1415[/C][C]0.129064[/C][/ROW]
[ROW][C]33[/C][C]-0.065712[/C][C]-0.5132[/C][C]0.304824[/C][/ROW]
[ROW][C]34[/C][C]-0.103258[/C][C]-0.8065[/C][C]0.211552[/C][/ROW]
[ROW][C]35[/C][C]0.054471[/C][C]0.4254[/C][C]0.33601[/C][/ROW]
[ROW][C]36[/C][C]0.294006[/C][C]2.2963[/C][C]0.012555[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61853&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61853&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
1-0.165425-1.2920.100613
2-0.282957-2.210.015435
3-0.095692-0.74740.228853
4-0.119485-0.93320.177196
50.0883640.69010.24636
60.1758091.37310.087372
70.1181690.92290.17984
8-0.164894-1.28790.101329
9-0.074602-0.58270.281136
10-0.2993-2.33760.011352
11-0.002969-0.02320.490788
120.7288455.69250
13-0.146753-1.14620.1281
14-0.221654-1.73120.044238
15-0.071423-0.55780.289502
16-0.099748-0.77910.219479
170.077260.60340.274233
180.1309671.02290.155202
190.1079160.84290.201302
20-0.156461-1.2220.113205
21-0.075618-0.59060.278486
22-0.208468-1.62820.05432
230.0460640.35980.36013
240.5178054.04427.5e-05
25-0.103631-0.80940.210719
26-0.200681-1.56740.061101
27-0.026017-0.20320.419827
28-0.069278-0.54110.295213
290.0673070.52570.300506
300.0766810.59890.275729
310.0963980.75290.227206
32-0.146152-1.14150.129064
33-0.065712-0.51320.304824
34-0.103258-0.80650.211552
350.0544710.42540.33601
360.2940062.29630.012555






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.165425-1.2920.100613
2-0.319053-2.49190.00772
3-0.240623-1.87930.03249
4-0.355573-2.77710.003638
5-0.225161-1.75860.041834
6-0.086422-0.6750.251119
70.0906970.70840.240709
8-0.051649-0.40340.344035
90.0261980.20460.419279
10-0.423649-3.30880.000788
11-0.510286-3.98559.1e-05
120.4018823.13880.001307
130.0668120.52180.301843
140.0492360.38450.350955
150.1024240.80.213419
160.0360150.28130.389721
170.0804410.62830.266087
18-0.101888-0.79580.214626
19-0.099198-0.77480.220738
20-0.100254-0.7830.218326
21-0.122157-0.95410.171905
220.0658440.51430.304465
23-0.030584-0.23890.406004
24-0.033181-0.25920.398195
250.0760750.59420.277299
26-0.080255-0.62680.266561
270.0459730.35910.360394
28-0.005495-0.04290.482953
290.0144770.11310.455174
30-0.023724-0.18530.426809
31-0.035916-0.28050.390015
32-0.0142-0.11090.456027
33-0.026277-0.20520.419038
340.0469940.3670.357431
350.0808020.63110.265171
36-0.205037-1.60140.057228

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.165425 & -1.292 & 0.100613 \tabularnewline
2 & -0.319053 & -2.4919 & 0.00772 \tabularnewline
3 & -0.240623 & -1.8793 & 0.03249 \tabularnewline
4 & -0.355573 & -2.7771 & 0.003638 \tabularnewline
5 & -0.225161 & -1.7586 & 0.041834 \tabularnewline
6 & -0.086422 & -0.675 & 0.251119 \tabularnewline
7 & 0.090697 & 0.7084 & 0.240709 \tabularnewline
8 & -0.051649 & -0.4034 & 0.344035 \tabularnewline
9 & 0.026198 & 0.2046 & 0.419279 \tabularnewline
10 & -0.423649 & -3.3088 & 0.000788 \tabularnewline
11 & -0.510286 & -3.9855 & 9.1e-05 \tabularnewline
12 & 0.401882 & 3.1388 & 0.001307 \tabularnewline
13 & 0.066812 & 0.5218 & 0.301843 \tabularnewline
14 & 0.049236 & 0.3845 & 0.350955 \tabularnewline
15 & 0.102424 & 0.8 & 0.213419 \tabularnewline
16 & 0.036015 & 0.2813 & 0.389721 \tabularnewline
17 & 0.080441 & 0.6283 & 0.266087 \tabularnewline
18 & -0.101888 & -0.7958 & 0.214626 \tabularnewline
19 & -0.099198 & -0.7748 & 0.220738 \tabularnewline
20 & -0.100254 & -0.783 & 0.218326 \tabularnewline
21 & -0.122157 & -0.9541 & 0.171905 \tabularnewline
22 & 0.065844 & 0.5143 & 0.304465 \tabularnewline
23 & -0.030584 & -0.2389 & 0.406004 \tabularnewline
24 & -0.033181 & -0.2592 & 0.398195 \tabularnewline
25 & 0.076075 & 0.5942 & 0.277299 \tabularnewline
26 & -0.080255 & -0.6268 & 0.266561 \tabularnewline
27 & 0.045973 & 0.3591 & 0.360394 \tabularnewline
28 & -0.005495 & -0.0429 & 0.482953 \tabularnewline
29 & 0.014477 & 0.1131 & 0.455174 \tabularnewline
30 & -0.023724 & -0.1853 & 0.426809 \tabularnewline
31 & -0.035916 & -0.2805 & 0.390015 \tabularnewline
32 & -0.0142 & -0.1109 & 0.456027 \tabularnewline
33 & -0.026277 & -0.2052 & 0.419038 \tabularnewline
34 & 0.046994 & 0.367 & 0.357431 \tabularnewline
35 & 0.080802 & 0.6311 & 0.265171 \tabularnewline
36 & -0.205037 & -1.6014 & 0.057228 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61853&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]-0.165425[/C][C]-1.292[/C][C]0.100613[/C][/ROW]
[ROW][C]2[/C][C]-0.319053[/C][C]-2.4919[/C][C]0.00772[/C][/ROW]
[ROW][C]3[/C][C]-0.240623[/C][C]-1.8793[/C][C]0.03249[/C][/ROW]
[ROW][C]4[/C][C]-0.355573[/C][C]-2.7771[/C][C]0.003638[/C][/ROW]
[ROW][C]5[/C][C]-0.225161[/C][C]-1.7586[/C][C]0.041834[/C][/ROW]
[ROW][C]6[/C][C]-0.086422[/C][C]-0.675[/C][C]0.251119[/C][/ROW]
[ROW][C]7[/C][C]0.090697[/C][C]0.7084[/C][C]0.240709[/C][/ROW]
[ROW][C]8[/C][C]-0.051649[/C][C]-0.4034[/C][C]0.344035[/C][/ROW]
[ROW][C]9[/C][C]0.026198[/C][C]0.2046[/C][C]0.419279[/C][/ROW]
[ROW][C]10[/C][C]-0.423649[/C][C]-3.3088[/C][C]0.000788[/C][/ROW]
[ROW][C]11[/C][C]-0.510286[/C][C]-3.9855[/C][C]9.1e-05[/C][/ROW]
[ROW][C]12[/C][C]0.401882[/C][C]3.1388[/C][C]0.001307[/C][/ROW]
[ROW][C]13[/C][C]0.066812[/C][C]0.5218[/C][C]0.301843[/C][/ROW]
[ROW][C]14[/C][C]0.049236[/C][C]0.3845[/C][C]0.350955[/C][/ROW]
[ROW][C]15[/C][C]0.102424[/C][C]0.8[/C][C]0.213419[/C][/ROW]
[ROW][C]16[/C][C]0.036015[/C][C]0.2813[/C][C]0.389721[/C][/ROW]
[ROW][C]17[/C][C]0.080441[/C][C]0.6283[/C][C]0.266087[/C][/ROW]
[ROW][C]18[/C][C]-0.101888[/C][C]-0.7958[/C][C]0.214626[/C][/ROW]
[ROW][C]19[/C][C]-0.099198[/C][C]-0.7748[/C][C]0.220738[/C][/ROW]
[ROW][C]20[/C][C]-0.100254[/C][C]-0.783[/C][C]0.218326[/C][/ROW]
[ROW][C]21[/C][C]-0.122157[/C][C]-0.9541[/C][C]0.171905[/C][/ROW]
[ROW][C]22[/C][C]0.065844[/C][C]0.5143[/C][C]0.304465[/C][/ROW]
[ROW][C]23[/C][C]-0.030584[/C][C]-0.2389[/C][C]0.406004[/C][/ROW]
[ROW][C]24[/C][C]-0.033181[/C][C]-0.2592[/C][C]0.398195[/C][/ROW]
[ROW][C]25[/C][C]0.076075[/C][C]0.5942[/C][C]0.277299[/C][/ROW]
[ROW][C]26[/C][C]-0.080255[/C][C]-0.6268[/C][C]0.266561[/C][/ROW]
[ROW][C]27[/C][C]0.045973[/C][C]0.3591[/C][C]0.360394[/C][/ROW]
[ROW][C]28[/C][C]-0.005495[/C][C]-0.0429[/C][C]0.482953[/C][/ROW]
[ROW][C]29[/C][C]0.014477[/C][C]0.1131[/C][C]0.455174[/C][/ROW]
[ROW][C]30[/C][C]-0.023724[/C][C]-0.1853[/C][C]0.426809[/C][/ROW]
[ROW][C]31[/C][C]-0.035916[/C][C]-0.2805[/C][C]0.390015[/C][/ROW]
[ROW][C]32[/C][C]-0.0142[/C][C]-0.1109[/C][C]0.456027[/C][/ROW]
[ROW][C]33[/C][C]-0.026277[/C][C]-0.2052[/C][C]0.419038[/C][/ROW]
[ROW][C]34[/C][C]0.046994[/C][C]0.367[/C][C]0.357431[/C][/ROW]
[ROW][C]35[/C][C]0.080802[/C][C]0.6311[/C][C]0.265171[/C][/ROW]
[ROW][C]36[/C][C]-0.205037[/C][C]-1.6014[/C][C]0.057228[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61853&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61853&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
1-0.165425-1.2920.100613
2-0.319053-2.49190.00772
3-0.240623-1.87930.03249
4-0.355573-2.77710.003638
5-0.225161-1.75860.041834
6-0.086422-0.6750.251119
70.0906970.70840.240709
8-0.051649-0.40340.344035
90.0261980.20460.419279
10-0.423649-3.30880.000788
11-0.510286-3.98559.1e-05
120.4018823.13880.001307
130.0668120.52180.301843
140.0492360.38450.350955
150.1024240.80.213419
160.0360150.28130.389721
170.0804410.62830.266087
18-0.101888-0.79580.214626
19-0.099198-0.77480.220738
20-0.100254-0.7830.218326
21-0.122157-0.95410.171905
220.0658440.51430.304465
23-0.030584-0.23890.406004
24-0.033181-0.25920.398195
250.0760750.59420.277299
26-0.080255-0.62680.266561
270.0459730.35910.360394
28-0.005495-0.04290.482953
290.0144770.11310.455174
30-0.023724-0.18530.426809
31-0.035916-0.28050.390015
32-0.0142-0.11090.456027
33-0.026277-0.20520.419038
340.0469940.3670.357431
350.0808020.63110.265171
36-0.205037-1.60140.057228


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')