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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 computationFri, 18 Dec 2009 06:44:34 -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/18/t12611444819oh8d47exq4oqto.htm/, Retrieved Sat, 27 Apr 2024 21:11:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69331, Retrieved Sat, 27 Apr 2024 21:11:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

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]
- R  D          [(Partial) Autocorrelation Function] [] [2009-12-18 13:44:34] [21edaefb91319406e70b6c03c71b58b3] [Current]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-18 14:21:24] [ea26ab7ea3bba830cfeb08d06278d52c]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
476
475
470
461
455
456
517
525
523
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581
564
558

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69331&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]3 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=69331&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69331&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8930848.70470
20.7377627.19080
30.6186896.03020
40.5507295.36780
50.5256035.12291e-06
60.4898434.77443e-06
70.4403314.29182.1e-05
80.3798633.70240.000179
90.3595243.50420.00035
100.3883153.78480.000135
110.4503424.38941.5e-05
120.4692554.57377e-06
130.3434433.34750.000585
140.1820091.7740.039633
150.0537710.52410.300718
16-0.020529-0.20010.42092
17-0.052275-0.50950.305788
18-0.088374-0.86140.195605
19-0.126645-1.23440.110053
20-0.171465-1.67120.048983
21-0.177389-1.7290.043531
22-0.142519-1.38910.084024
23-0.088343-0.86110.195687
24-0.070284-0.6850.247492
25-0.167558-1.63320.052874
26-0.290445-2.83090.002833
27-0.38023-3.7060.000177
28-0.425417-4.14653.7e-05
29-0.434565-4.23562.6e-05
30-0.443074-4.31851.9e-05
31-0.450286-4.38881.5e-05
32-0.456976-4.45411.1e-05
33-0.425877-4.15093.6e-05
34-0.359984-3.50870.000345
35-0.285284-2.78060.003271
36-0.241971-2.35840.010201

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.893084 & 8.7047 & 0 \tabularnewline
2 & 0.737762 & 7.1908 & 0 \tabularnewline
3 & 0.618689 & 6.0302 & 0 \tabularnewline
4 & 0.550729 & 5.3678 & 0 \tabularnewline
5 & 0.525603 & 5.1229 & 1e-06 \tabularnewline
6 & 0.489843 & 4.7744 & 3e-06 \tabularnewline
7 & 0.440331 & 4.2918 & 2.1e-05 \tabularnewline
8 & 0.379863 & 3.7024 & 0.000179 \tabularnewline
9 & 0.359524 & 3.5042 & 0.00035 \tabularnewline
10 & 0.388315 & 3.7848 & 0.000135 \tabularnewline
11 & 0.450342 & 4.3894 & 1.5e-05 \tabularnewline
12 & 0.469255 & 4.5737 & 7e-06 \tabularnewline
13 & 0.343443 & 3.3475 & 0.000585 \tabularnewline
14 & 0.182009 & 1.774 & 0.039633 \tabularnewline
15 & 0.053771 & 0.5241 & 0.300718 \tabularnewline
16 & -0.020529 & -0.2001 & 0.42092 \tabularnewline
17 & -0.052275 & -0.5095 & 0.305788 \tabularnewline
18 & -0.088374 & -0.8614 & 0.195605 \tabularnewline
19 & -0.126645 & -1.2344 & 0.110053 \tabularnewline
20 & -0.171465 & -1.6712 & 0.048983 \tabularnewline
21 & -0.177389 & -1.729 & 0.043531 \tabularnewline
22 & -0.142519 & -1.3891 & 0.084024 \tabularnewline
23 & -0.088343 & -0.8611 & 0.195687 \tabularnewline
24 & -0.070284 & -0.685 & 0.247492 \tabularnewline
25 & -0.167558 & -1.6332 & 0.052874 \tabularnewline
26 & -0.290445 & -2.8309 & 0.002833 \tabularnewline
27 & -0.38023 & -3.706 & 0.000177 \tabularnewline
28 & -0.425417 & -4.1465 & 3.7e-05 \tabularnewline
29 & -0.434565 & -4.2356 & 2.6e-05 \tabularnewline
30 & -0.443074 & -4.3185 & 1.9e-05 \tabularnewline
31 & -0.450286 & -4.3888 & 1.5e-05 \tabularnewline
32 & -0.456976 & -4.4541 & 1.1e-05 \tabularnewline
33 & -0.425877 & -4.1509 & 3.6e-05 \tabularnewline
34 & -0.359984 & -3.5087 & 0.000345 \tabularnewline
35 & -0.285284 & -2.7806 & 0.003271 \tabularnewline
36 & -0.241971 & -2.3584 & 0.010201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69331&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]0.893084[/C][C]8.7047[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.737762[/C][C]7.1908[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.618689[/C][C]6.0302[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.550729[/C][C]5.3678[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.525603[/C][C]5.1229[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.489843[/C][C]4.7744[/C][C]3e-06[/C][/ROW]
[ROW][C]7[/C][C]0.440331[/C][C]4.2918[/C][C]2.1e-05[/C][/ROW]
[ROW][C]8[/C][C]0.379863[/C][C]3.7024[/C][C]0.000179[/C][/ROW]
[ROW][C]9[/C][C]0.359524[/C][C]3.5042[/C][C]0.00035[/C][/ROW]
[ROW][C]10[/C][C]0.388315[/C][C]3.7848[/C][C]0.000135[/C][/ROW]
[ROW][C]11[/C][C]0.450342[/C][C]4.3894[/C][C]1.5e-05[/C][/ROW]
[ROW][C]12[/C][C]0.469255[/C][C]4.5737[/C][C]7e-06[/C][/ROW]
[ROW][C]13[/C][C]0.343443[/C][C]3.3475[/C][C]0.000585[/C][/ROW]
[ROW][C]14[/C][C]0.182009[/C][C]1.774[/C][C]0.039633[/C][/ROW]
[ROW][C]15[/C][C]0.053771[/C][C]0.5241[/C][C]0.300718[/C][/ROW]
[ROW][C]16[/C][C]-0.020529[/C][C]-0.2001[/C][C]0.42092[/C][/ROW]
[ROW][C]17[/C][C]-0.052275[/C][C]-0.5095[/C][C]0.305788[/C][/ROW]
[ROW][C]18[/C][C]-0.088374[/C][C]-0.8614[/C][C]0.195605[/C][/ROW]
[ROW][C]19[/C][C]-0.126645[/C][C]-1.2344[/C][C]0.110053[/C][/ROW]
[ROW][C]20[/C][C]-0.171465[/C][C]-1.6712[/C][C]0.048983[/C][/ROW]
[ROW][C]21[/C][C]-0.177389[/C][C]-1.729[/C][C]0.043531[/C][/ROW]
[ROW][C]22[/C][C]-0.142519[/C][C]-1.3891[/C][C]0.084024[/C][/ROW]
[ROW][C]23[/C][C]-0.088343[/C][C]-0.8611[/C][C]0.195687[/C][/ROW]
[ROW][C]24[/C][C]-0.070284[/C][C]-0.685[/C][C]0.247492[/C][/ROW]
[ROW][C]25[/C][C]-0.167558[/C][C]-1.6332[/C][C]0.052874[/C][/ROW]
[ROW][C]26[/C][C]-0.290445[/C][C]-2.8309[/C][C]0.002833[/C][/ROW]
[ROW][C]27[/C][C]-0.38023[/C][C]-3.706[/C][C]0.000177[/C][/ROW]
[ROW][C]28[/C][C]-0.425417[/C][C]-4.1465[/C][C]3.7e-05[/C][/ROW]
[ROW][C]29[/C][C]-0.434565[/C][C]-4.2356[/C][C]2.6e-05[/C][/ROW]
[ROW][C]30[/C][C]-0.443074[/C][C]-4.3185[/C][C]1.9e-05[/C][/ROW]
[ROW][C]31[/C][C]-0.450286[/C][C]-4.3888[/C][C]1.5e-05[/C][/ROW]
[ROW][C]32[/C][C]-0.456976[/C][C]-4.4541[/C][C]1.1e-05[/C][/ROW]
[ROW][C]33[/C][C]-0.425877[/C][C]-4.1509[/C][C]3.6e-05[/C][/ROW]
[ROW][C]34[/C][C]-0.359984[/C][C]-3.5087[/C][C]0.000345[/C][/ROW]
[ROW][C]35[/C][C]-0.285284[/C][C]-2.7806[/C][C]0.003271[/C][/ROW]
[ROW][C]36[/C][C]-0.241971[/C][C]-2.3584[/C][C]0.010201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69331&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69331&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
10.8930848.70470
20.7377627.19080
30.6186896.03020
40.5507295.36780
50.5256035.12291e-06
60.4898434.77443e-06
70.4403314.29182.1e-05
80.3798633.70240.000179
90.3595243.50420.00035
100.3883153.78480.000135
110.4503424.38941.5e-05
120.4692554.57377e-06
130.3434433.34750.000585
140.1820091.7740.039633
150.0537710.52410.300718
16-0.020529-0.20010.42092
17-0.052275-0.50950.305788
18-0.088374-0.86140.195605
19-0.126645-1.23440.110053
20-0.171465-1.67120.048983
21-0.177389-1.7290.043531
22-0.142519-1.38910.084024
23-0.088343-0.86110.195687
24-0.070284-0.6850.247492
25-0.167558-1.63320.052874
26-0.290445-2.83090.002833
27-0.38023-3.7060.000177
28-0.425417-4.14653.7e-05
29-0.434565-4.23562.6e-05
30-0.443074-4.31851.9e-05
31-0.450286-4.38881.5e-05
32-0.456976-4.45411.1e-05
33-0.425877-4.15093.6e-05
34-0.359984-3.50870.000345
35-0.285284-2.78060.003271
36-0.241971-2.35840.010201






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8930848.70470
2-0.295632-2.88150.002447
30.157231.53250.064363
40.0998690.97340.166413
50.1168771.13920.128747
6-0.107322-1.0460.149097
70.026730.26050.397508
8-0.053439-0.52090.301838
90.217652.12140.018246
100.1100921.0730.142985
110.1881571.83390.034898
12-0.202104-1.96990.025883
13-0.585401-5.70580
140.0070330.06860.472745
15-0.05938-0.57880.28206
16-0.011063-0.10780.457179
17-0.023093-0.22510.411198
18-0.002236-0.02180.491331
190.0852040.83050.20418
20-0.016304-0.15890.437038
210.0467170.45530.324953
22-0.056365-0.54940.292018
23-0.056835-0.5540.290455
24-0.010439-0.10170.459587
25-0.170807-1.66480.049622
260.0093650.09130.463732
27-0.019546-0.19050.424656
28-0.082755-0.80660.210957
29-0.021209-0.20670.418334
30-0.006627-0.06460.474319
31-0.00997-0.09720.461396
320.0184220.17960.428941
330.0129960.12670.449735
340.0208860.20360.419561
35-0.030653-0.29880.382885
360.0338110.32960.371232

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.893084 & 8.7047 & 0 \tabularnewline
2 & -0.295632 & -2.8815 & 0.002447 \tabularnewline
3 & 0.15723 & 1.5325 & 0.064363 \tabularnewline
4 & 0.099869 & 0.9734 & 0.166413 \tabularnewline
5 & 0.116877 & 1.1392 & 0.128747 \tabularnewline
6 & -0.107322 & -1.046 & 0.149097 \tabularnewline
7 & 0.02673 & 0.2605 & 0.397508 \tabularnewline
8 & -0.053439 & -0.5209 & 0.301838 \tabularnewline
9 & 0.21765 & 2.1214 & 0.018246 \tabularnewline
10 & 0.110092 & 1.073 & 0.142985 \tabularnewline
11 & 0.188157 & 1.8339 & 0.034898 \tabularnewline
12 & -0.202104 & -1.9699 & 0.025883 \tabularnewline
13 & -0.585401 & -5.7058 & 0 \tabularnewline
14 & 0.007033 & 0.0686 & 0.472745 \tabularnewline
15 & -0.05938 & -0.5788 & 0.28206 \tabularnewline
16 & -0.011063 & -0.1078 & 0.457179 \tabularnewline
17 & -0.023093 & -0.2251 & 0.411198 \tabularnewline
18 & -0.002236 & -0.0218 & 0.491331 \tabularnewline
19 & 0.085204 & 0.8305 & 0.20418 \tabularnewline
20 & -0.016304 & -0.1589 & 0.437038 \tabularnewline
21 & 0.046717 & 0.4553 & 0.324953 \tabularnewline
22 & -0.056365 & -0.5494 & 0.292018 \tabularnewline
23 & -0.056835 & -0.554 & 0.290455 \tabularnewline
24 & -0.010439 & -0.1017 & 0.459587 \tabularnewline
25 & -0.170807 & -1.6648 & 0.049622 \tabularnewline
26 & 0.009365 & 0.0913 & 0.463732 \tabularnewline
27 & -0.019546 & -0.1905 & 0.424656 \tabularnewline
28 & -0.082755 & -0.8066 & 0.210957 \tabularnewline
29 & -0.021209 & -0.2067 & 0.418334 \tabularnewline
30 & -0.006627 & -0.0646 & 0.474319 \tabularnewline
31 & -0.00997 & -0.0972 & 0.461396 \tabularnewline
32 & 0.018422 & 0.1796 & 0.428941 \tabularnewline
33 & 0.012996 & 0.1267 & 0.449735 \tabularnewline
34 & 0.020886 & 0.2036 & 0.419561 \tabularnewline
35 & -0.030653 & -0.2988 & 0.382885 \tabularnewline
36 & 0.033811 & 0.3296 & 0.371232 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69331&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]0.893084[/C][C]8.7047[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.295632[/C][C]-2.8815[/C][C]0.002447[/C][/ROW]
[ROW][C]3[/C][C]0.15723[/C][C]1.5325[/C][C]0.064363[/C][/ROW]
[ROW][C]4[/C][C]0.099869[/C][C]0.9734[/C][C]0.166413[/C][/ROW]
[ROW][C]5[/C][C]0.116877[/C][C]1.1392[/C][C]0.128747[/C][/ROW]
[ROW][C]6[/C][C]-0.107322[/C][C]-1.046[/C][C]0.149097[/C][/ROW]
[ROW][C]7[/C][C]0.02673[/C][C]0.2605[/C][C]0.397508[/C][/ROW]
[ROW][C]8[/C][C]-0.053439[/C][C]-0.5209[/C][C]0.301838[/C][/ROW]
[ROW][C]9[/C][C]0.21765[/C][C]2.1214[/C][C]0.018246[/C][/ROW]
[ROW][C]10[/C][C]0.110092[/C][C]1.073[/C][C]0.142985[/C][/ROW]
[ROW][C]11[/C][C]0.188157[/C][C]1.8339[/C][C]0.034898[/C][/ROW]
[ROW][C]12[/C][C]-0.202104[/C][C]-1.9699[/C][C]0.025883[/C][/ROW]
[ROW][C]13[/C][C]-0.585401[/C][C]-5.7058[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.007033[/C][C]0.0686[/C][C]0.472745[/C][/ROW]
[ROW][C]15[/C][C]-0.05938[/C][C]-0.5788[/C][C]0.28206[/C][/ROW]
[ROW][C]16[/C][C]-0.011063[/C][C]-0.1078[/C][C]0.457179[/C][/ROW]
[ROW][C]17[/C][C]-0.023093[/C][C]-0.2251[/C][C]0.411198[/C][/ROW]
[ROW][C]18[/C][C]-0.002236[/C][C]-0.0218[/C][C]0.491331[/C][/ROW]
[ROW][C]19[/C][C]0.085204[/C][C]0.8305[/C][C]0.20418[/C][/ROW]
[ROW][C]20[/C][C]-0.016304[/C][C]-0.1589[/C][C]0.437038[/C][/ROW]
[ROW][C]21[/C][C]0.046717[/C][C]0.4553[/C][C]0.324953[/C][/ROW]
[ROW][C]22[/C][C]-0.056365[/C][C]-0.5494[/C][C]0.292018[/C][/ROW]
[ROW][C]23[/C][C]-0.056835[/C][C]-0.554[/C][C]0.290455[/C][/ROW]
[ROW][C]24[/C][C]-0.010439[/C][C]-0.1017[/C][C]0.459587[/C][/ROW]
[ROW][C]25[/C][C]-0.170807[/C][C]-1.6648[/C][C]0.049622[/C][/ROW]
[ROW][C]26[/C][C]0.009365[/C][C]0.0913[/C][C]0.463732[/C][/ROW]
[ROW][C]27[/C][C]-0.019546[/C][C]-0.1905[/C][C]0.424656[/C][/ROW]
[ROW][C]28[/C][C]-0.082755[/C][C]-0.8066[/C][C]0.210957[/C][/ROW]
[ROW][C]29[/C][C]-0.021209[/C][C]-0.2067[/C][C]0.418334[/C][/ROW]
[ROW][C]30[/C][C]-0.006627[/C][C]-0.0646[/C][C]0.474319[/C][/ROW]
[ROW][C]31[/C][C]-0.00997[/C][C]-0.0972[/C][C]0.461396[/C][/ROW]
[ROW][C]32[/C][C]0.018422[/C][C]0.1796[/C][C]0.428941[/C][/ROW]
[ROW][C]33[/C][C]0.012996[/C][C]0.1267[/C][C]0.449735[/C][/ROW]
[ROW][C]34[/C][C]0.020886[/C][C]0.2036[/C][C]0.419561[/C][/ROW]
[ROW][C]35[/C][C]-0.030653[/C][C]-0.2988[/C][C]0.382885[/C][/ROW]
[ROW][C]36[/C][C]0.033811[/C][C]0.3296[/C][C]0.371232[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69331&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69331&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
10.8930848.70470
2-0.295632-2.88150.002447
30.157231.53250.064363
40.0998690.97340.166413
50.1168771.13920.128747
6-0.107322-1.0460.149097
70.026730.26050.397508
8-0.053439-0.52090.301838
90.217652.12140.018246
100.1100921.0730.142985
110.1881571.83390.034898
12-0.202104-1.96990.025883
13-0.585401-5.70580
140.0070330.06860.472745
15-0.05938-0.57880.28206
16-0.011063-0.10780.457179
17-0.023093-0.22510.411198
18-0.002236-0.02180.491331
190.0852040.83050.20418
20-0.016304-0.15890.437038
210.0467170.45530.324953
22-0.056365-0.54940.292018
23-0.056835-0.5540.290455
24-0.010439-0.10170.459587
25-0.170807-1.66480.049622
260.0093650.09130.463732
27-0.019546-0.19050.424656
28-0.082755-0.80660.210957
29-0.021209-0.20670.418334
30-0.006627-0.06460.474319
31-0.00997-0.09720.461396
320.0184220.17960.428941
330.0129960.12670.449735
340.0208860.20360.419561
35-0.030653-0.29880.382885
360.0338110.32960.371232


Figures (Output of Computation)

Input Parameters & R Code

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