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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 15:50:11 -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/t1259880653v1j27chvhr5zmpe.htm/, Retrieved Wed, 02 Apr 2025 08:49:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63142, Retrieved Wed, 02 Apr 2025 08:49:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact258

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]
-    D        [(Partial) Autocorrelation Function] [Autocorrelatie fu...] [2009-11-23 18:29:14] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-    D            [(Partial) Autocorrelation Function] [ACF met: d=0, D=0...] [2009-12-03 22:50:11] [371dc2189c569d90e2c1567f632c3ec0] [Current]
-    D              [(Partial) Autocorrelation Function] [ACF met: d=0, D=0...] [2009-12-16 22:39:45] [34d27ebe78dc2d31581e8710befe8733]
-   P                 [(Partial) Autocorrelation Function] [ACF met: d=0, D=0...] [2009-12-19 11:26:01] [34d27ebe78dc2d31581e8710befe8733]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418
412
404
409
412
406
398
397
385
390
413
413
401
397
397
409
419
424
428
430
424
433
456
459
446
441

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63142&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]2 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=63142&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63142&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9363947.31350
20.8534936.6660
30.8009166.25540
40.7739136.04450
50.7579635.91990
60.7206575.62850
70.6454655.04122e-06
80.5491594.28913.3e-05
90.4688523.66180.000263
100.4153543.2440.000957
110.3987013.1140.001405
120.360282.81390.00329
130.2522181.96990.026698
140.1441311.12570.13235
150.0662970.51780.303238
160.0140110.10940.456611
17-0.019828-0.15490.43872
18-0.061473-0.48010.31643
19-0.126824-0.99050.162915
20-0.210428-1.64350.052713
21-0.270713-2.11430.019291
22-0.304843-2.38090.010204
23-0.313739-2.45040.008577
24-0.337882-2.63890.005271
25-0.396131-3.09390.00149
26-0.445993-3.48330.000461
27-0.464779-3.630.000291
28-0.462719-3.61390.000306
29-0.441872-3.45110.00051
30-0.420129-3.28130.000856
31-0.413681-3.2310.000995
32-0.416517-3.25310.000931
33-0.394022-3.07740.001563
34-0.363989-2.84280.003037
35-0.330077-2.5780.006184
36-0.302128-2.35970.010753

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936394 & 7.3135 & 0 \tabularnewline
2 & 0.853493 & 6.666 & 0 \tabularnewline
3 & 0.800916 & 6.2554 & 0 \tabularnewline
4 & 0.773913 & 6.0445 & 0 \tabularnewline
5 & 0.757963 & 5.9199 & 0 \tabularnewline
6 & 0.720657 & 5.6285 & 0 \tabularnewline
7 & 0.645465 & 5.0412 & 2e-06 \tabularnewline
8 & 0.549159 & 4.2891 & 3.3e-05 \tabularnewline
9 & 0.468852 & 3.6618 & 0.000263 \tabularnewline
10 & 0.415354 & 3.244 & 0.000957 \tabularnewline
11 & 0.398701 & 3.114 & 0.001405 \tabularnewline
12 & 0.36028 & 2.8139 & 0.00329 \tabularnewline
13 & 0.252218 & 1.9699 & 0.026698 \tabularnewline
14 & 0.144131 & 1.1257 & 0.13235 \tabularnewline
15 & 0.066297 & 0.5178 & 0.303238 \tabularnewline
16 & 0.014011 & 0.1094 & 0.456611 \tabularnewline
17 & -0.019828 & -0.1549 & 0.43872 \tabularnewline
18 & -0.061473 & -0.4801 & 0.31643 \tabularnewline
19 & -0.126824 & -0.9905 & 0.162915 \tabularnewline
20 & -0.210428 & -1.6435 & 0.052713 \tabularnewline
21 & -0.270713 & -2.1143 & 0.019291 \tabularnewline
22 & -0.304843 & -2.3809 & 0.010204 \tabularnewline
23 & -0.313739 & -2.4504 & 0.008577 \tabularnewline
24 & -0.337882 & -2.6389 & 0.005271 \tabularnewline
25 & -0.396131 & -3.0939 & 0.00149 \tabularnewline
26 & -0.445993 & -3.4833 & 0.000461 \tabularnewline
27 & -0.464779 & -3.63 & 0.000291 \tabularnewline
28 & -0.462719 & -3.6139 & 0.000306 \tabularnewline
29 & -0.441872 & -3.4511 & 0.00051 \tabularnewline
30 & -0.420129 & -3.2813 & 0.000856 \tabularnewline
31 & -0.413681 & -3.231 & 0.000995 \tabularnewline
32 & -0.416517 & -3.2531 & 0.000931 \tabularnewline
33 & -0.394022 & -3.0774 & 0.001563 \tabularnewline
34 & -0.363989 & -2.8428 & 0.003037 \tabularnewline
35 & -0.330077 & -2.578 & 0.006184 \tabularnewline
36 & -0.302128 & -2.3597 & 0.010753 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63142&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]0.936394[/C][C]7.3135[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.853493[/C][C]6.666[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.800916[/C][C]6.2554[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.773913[/C][C]6.0445[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.757963[/C][C]5.9199[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.720657[/C][C]5.6285[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.645465[/C][C]5.0412[/C][C]2e-06[/C][/ROW]
[ROW][C]8[/C][C]0.549159[/C][C]4.2891[/C][C]3.3e-05[/C][/ROW]
[ROW][C]9[/C][C]0.468852[/C][C]3.6618[/C][C]0.000263[/C][/ROW]
[ROW][C]10[/C][C]0.415354[/C][C]3.244[/C][C]0.000957[/C][/ROW]
[ROW][C]11[/C][C]0.398701[/C][C]3.114[/C][C]0.001405[/C][/ROW]
[ROW][C]12[/C][C]0.36028[/C][C]2.8139[/C][C]0.00329[/C][/ROW]
[ROW][C]13[/C][C]0.252218[/C][C]1.9699[/C][C]0.026698[/C][/ROW]
[ROW][C]14[/C][C]0.144131[/C][C]1.1257[/C][C]0.13235[/C][/ROW]
[ROW][C]15[/C][C]0.066297[/C][C]0.5178[/C][C]0.303238[/C][/ROW]
[ROW][C]16[/C][C]0.014011[/C][C]0.1094[/C][C]0.456611[/C][/ROW]
[ROW][C]17[/C][C]-0.019828[/C][C]-0.1549[/C][C]0.43872[/C][/ROW]
[ROW][C]18[/C][C]-0.061473[/C][C]-0.4801[/C][C]0.31643[/C][/ROW]
[ROW][C]19[/C][C]-0.126824[/C][C]-0.9905[/C][C]0.162915[/C][/ROW]
[ROW][C]20[/C][C]-0.210428[/C][C]-1.6435[/C][C]0.052713[/C][/ROW]
[ROW][C]21[/C][C]-0.270713[/C][C]-2.1143[/C][C]0.019291[/C][/ROW]
[ROW][C]22[/C][C]-0.304843[/C][C]-2.3809[/C][C]0.010204[/C][/ROW]
[ROW][C]23[/C][C]-0.313739[/C][C]-2.4504[/C][C]0.008577[/C][/ROW]
[ROW][C]24[/C][C]-0.337882[/C][C]-2.6389[/C][C]0.005271[/C][/ROW]
[ROW][C]25[/C][C]-0.396131[/C][C]-3.0939[/C][C]0.00149[/C][/ROW]
[ROW][C]26[/C][C]-0.445993[/C][C]-3.4833[/C][C]0.000461[/C][/ROW]
[ROW][C]27[/C][C]-0.464779[/C][C]-3.63[/C][C]0.000291[/C][/ROW]
[ROW][C]28[/C][C]-0.462719[/C][C]-3.6139[/C][C]0.000306[/C][/ROW]
[ROW][C]29[/C][C]-0.441872[/C][C]-3.4511[/C][C]0.00051[/C][/ROW]
[ROW][C]30[/C][C]-0.420129[/C][C]-3.2813[/C][C]0.000856[/C][/ROW]
[ROW][C]31[/C][C]-0.413681[/C][C]-3.231[/C][C]0.000995[/C][/ROW]
[ROW][C]32[/C][C]-0.416517[/C][C]-3.2531[/C][C]0.000931[/C][/ROW]
[ROW][C]33[/C][C]-0.394022[/C][C]-3.0774[/C][C]0.001563[/C][/ROW]
[ROW][C]34[/C][C]-0.363989[/C][C]-2.8428[/C][C]0.003037[/C][/ROW]
[ROW][C]35[/C][C]-0.330077[/C][C]-2.578[/C][C]0.006184[/C][/ROW]
[ROW][C]36[/C][C]-0.302128[/C][C]-2.3597[/C][C]0.010753[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63142&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63142&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
10.9363947.31350
20.8534936.6660
30.8009166.25540
40.7739136.04450
50.7579635.91990
60.7206575.62850
70.6454655.04122e-06
80.5491594.28913.3e-05
90.4688523.66180.000263
100.4153543.2440.000957
110.3987013.1140.001405
120.360282.81390.00329
130.2522181.96990.026698
140.1441311.12570.13235
150.0662970.51780.303238
160.0140110.10940.456611
17-0.019828-0.15490.43872
18-0.061473-0.48010.31643
19-0.126824-0.99050.162915
20-0.210428-1.64350.052713
21-0.270713-2.11430.019291
22-0.304843-2.38090.010204
23-0.313739-2.45040.008577
24-0.337882-2.63890.005271
25-0.396131-3.09390.00149
26-0.445993-3.48330.000461
27-0.464779-3.630.000291
28-0.462719-3.61390.000306
29-0.441872-3.45110.00051
30-0.420129-3.28130.000856
31-0.413681-3.2310.000995
32-0.416517-3.25310.000931
33-0.394022-3.07740.001563
34-0.363989-2.84280.003037
35-0.330077-2.5780.006184
36-0.302128-2.35970.010753






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9363947.31350
2-0.189507-1.48010.071997
30.233351.82250.036639
40.1021470.79780.214042
50.0854880.66770.253428
6-0.152188-1.18860.119596
7-0.242023-1.89030.031738
8-0.210634-1.64510.052546
9-0.032646-0.2550.399801
10-0.001759-0.01370.494543
110.2700282.1090.019529
12-0.176552-1.37890.086478
13-0.432044-3.37440.000645
140.0914850.71450.238816
15-0.019096-0.14910.440966
16-0.059871-0.46760.320866
170.0437030.34130.367015
180.0175270.13690.445784
190.0425930.33270.370264
20-0.143014-1.1170.134192
210.0879420.68680.247391
22-0.117506-0.91780.181182
23-0.100124-0.7820.218621
240.0102420.080.468251
250.0225940.17650.430256
260.0018290.01430.494324
270.1329311.03820.151631
28-0.032275-0.25210.400914
290.1014220.79210.215677
30-0.001615-0.01260.494988
310.0941190.73510.23255
32-0.011365-0.08880.464781
330.0597220.46640.32128
34-0.198434-1.54980.063179
35-0.074688-0.58330.280911
360.0229760.17940.429091

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.936394 & 7.3135 & 0 \tabularnewline
2 & -0.189507 & -1.4801 & 0.071997 \tabularnewline
3 & 0.23335 & 1.8225 & 0.036639 \tabularnewline
4 & 0.102147 & 0.7978 & 0.214042 \tabularnewline
5 & 0.085488 & 0.6677 & 0.253428 \tabularnewline
6 & -0.152188 & -1.1886 & 0.119596 \tabularnewline
7 & -0.242023 & -1.8903 & 0.031738 \tabularnewline
8 & -0.210634 & -1.6451 & 0.052546 \tabularnewline
9 & -0.032646 & -0.255 & 0.399801 \tabularnewline
10 & -0.001759 & -0.0137 & 0.494543 \tabularnewline
11 & 0.270028 & 2.109 & 0.019529 \tabularnewline
12 & -0.176552 & -1.3789 & 0.086478 \tabularnewline
13 & -0.432044 & -3.3744 & 0.000645 \tabularnewline
14 & 0.091485 & 0.7145 & 0.238816 \tabularnewline
15 & -0.019096 & -0.1491 & 0.440966 \tabularnewline
16 & -0.059871 & -0.4676 & 0.320866 \tabularnewline
17 & 0.043703 & 0.3413 & 0.367015 \tabularnewline
18 & 0.017527 & 0.1369 & 0.445784 \tabularnewline
19 & 0.042593 & 0.3327 & 0.370264 \tabularnewline
20 & -0.143014 & -1.117 & 0.134192 \tabularnewline
21 & 0.087942 & 0.6868 & 0.247391 \tabularnewline
22 & -0.117506 & -0.9178 & 0.181182 \tabularnewline
23 & -0.100124 & -0.782 & 0.218621 \tabularnewline
24 & 0.010242 & 0.08 & 0.468251 \tabularnewline
25 & 0.022594 & 0.1765 & 0.430256 \tabularnewline
26 & 0.001829 & 0.0143 & 0.494324 \tabularnewline
27 & 0.132931 & 1.0382 & 0.151631 \tabularnewline
28 & -0.032275 & -0.2521 & 0.400914 \tabularnewline
29 & 0.101422 & 0.7921 & 0.215677 \tabularnewline
30 & -0.001615 & -0.0126 & 0.494988 \tabularnewline
31 & 0.094119 & 0.7351 & 0.23255 \tabularnewline
32 & -0.011365 & -0.0888 & 0.464781 \tabularnewline
33 & 0.059722 & 0.4664 & 0.32128 \tabularnewline
34 & -0.198434 & -1.5498 & 0.063179 \tabularnewline
35 & -0.074688 & -0.5833 & 0.280911 \tabularnewline
36 & 0.022976 & 0.1794 & 0.429091 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63142&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]0.936394[/C][C]7.3135[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.189507[/C][C]-1.4801[/C][C]0.071997[/C][/ROW]
[ROW][C]3[/C][C]0.23335[/C][C]1.8225[/C][C]0.036639[/C][/ROW]
[ROW][C]4[/C][C]0.102147[/C][C]0.7978[/C][C]0.214042[/C][/ROW]
[ROW][C]5[/C][C]0.085488[/C][C]0.6677[/C][C]0.253428[/C][/ROW]
[ROW][C]6[/C][C]-0.152188[/C][C]-1.1886[/C][C]0.119596[/C][/ROW]
[ROW][C]7[/C][C]-0.242023[/C][C]-1.8903[/C][C]0.031738[/C][/ROW]
[ROW][C]8[/C][C]-0.210634[/C][C]-1.6451[/C][C]0.052546[/C][/ROW]
[ROW][C]9[/C][C]-0.032646[/C][C]-0.255[/C][C]0.399801[/C][/ROW]
[ROW][C]10[/C][C]-0.001759[/C][C]-0.0137[/C][C]0.494543[/C][/ROW]
[ROW][C]11[/C][C]0.270028[/C][C]2.109[/C][C]0.019529[/C][/ROW]
[ROW][C]12[/C][C]-0.176552[/C][C]-1.3789[/C][C]0.086478[/C][/ROW]
[ROW][C]13[/C][C]-0.432044[/C][C]-3.3744[/C][C]0.000645[/C][/ROW]
[ROW][C]14[/C][C]0.091485[/C][C]0.7145[/C][C]0.238816[/C][/ROW]
[ROW][C]15[/C][C]-0.019096[/C][C]-0.1491[/C][C]0.440966[/C][/ROW]
[ROW][C]16[/C][C]-0.059871[/C][C]-0.4676[/C][C]0.320866[/C][/ROW]
[ROW][C]17[/C][C]0.043703[/C][C]0.3413[/C][C]0.367015[/C][/ROW]
[ROW][C]18[/C][C]0.017527[/C][C]0.1369[/C][C]0.445784[/C][/ROW]
[ROW][C]19[/C][C]0.042593[/C][C]0.3327[/C][C]0.370264[/C][/ROW]
[ROW][C]20[/C][C]-0.143014[/C][C]-1.117[/C][C]0.134192[/C][/ROW]
[ROW][C]21[/C][C]0.087942[/C][C]0.6868[/C][C]0.247391[/C][/ROW]
[ROW][C]22[/C][C]-0.117506[/C][C]-0.9178[/C][C]0.181182[/C][/ROW]
[ROW][C]23[/C][C]-0.100124[/C][C]-0.782[/C][C]0.218621[/C][/ROW]
[ROW][C]24[/C][C]0.010242[/C][C]0.08[/C][C]0.468251[/C][/ROW]
[ROW][C]25[/C][C]0.022594[/C][C]0.1765[/C][C]0.430256[/C][/ROW]
[ROW][C]26[/C][C]0.001829[/C][C]0.0143[/C][C]0.494324[/C][/ROW]
[ROW][C]27[/C][C]0.132931[/C][C]1.0382[/C][C]0.151631[/C][/ROW]
[ROW][C]28[/C][C]-0.032275[/C][C]-0.2521[/C][C]0.400914[/C][/ROW]
[ROW][C]29[/C][C]0.101422[/C][C]0.7921[/C][C]0.215677[/C][/ROW]
[ROW][C]30[/C][C]-0.001615[/C][C]-0.0126[/C][C]0.494988[/C][/ROW]
[ROW][C]31[/C][C]0.094119[/C][C]0.7351[/C][C]0.23255[/C][/ROW]
[ROW][C]32[/C][C]-0.011365[/C][C]-0.0888[/C][C]0.464781[/C][/ROW]
[ROW][C]33[/C][C]0.059722[/C][C]0.4664[/C][C]0.32128[/C][/ROW]
[ROW][C]34[/C][C]-0.198434[/C][C]-1.5498[/C][C]0.063179[/C][/ROW]
[ROW][C]35[/C][C]-0.074688[/C][C]-0.5833[/C][C]0.280911[/C][/ROW]
[ROW][C]36[/C][C]0.022976[/C][C]0.1794[/C][C]0.429091[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63142&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63142&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
10.9363947.31350
2-0.189507-1.48010.071997
30.233351.82250.036639
40.1021470.79780.214042
50.0854880.66770.253428
6-0.152188-1.18860.119596
7-0.242023-1.89030.031738
8-0.210634-1.64510.052546
9-0.032646-0.2550.399801
10-0.001759-0.01370.494543
110.2700282.1090.019529
12-0.176552-1.37890.086478
13-0.432044-3.37440.000645
140.0914850.71450.238816
15-0.019096-0.14910.440966
16-0.059871-0.46760.320866
170.0437030.34130.367015
180.0175270.13690.445784
190.0425930.33270.370264
20-0.143014-1.1170.134192
210.0879420.68680.247391
22-0.117506-0.91780.181182
23-0.100124-0.7820.218621
240.0102420.080.468251
250.0225940.17650.430256
260.0018290.01430.494324
270.1329311.03820.151631
28-0.032275-0.25210.400914
290.1014220.79210.215677
30-0.001615-0.01260.494988
310.0941190.73510.23255
32-0.011365-0.08880.464781
330.0597220.46640.32128
34-0.198434-1.54980.063179
35-0.074688-0.58330.280911
360.0229760.17940.429091


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')