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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 computationMon, 14 Dec 2009 02:12:40 -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/14/t12607820528plac9q3qmzrzt8.htm/, Retrieved Tue, 07 May 2024 18:35:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67454, Retrieved Tue, 07 May 2024 18:35:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
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] [WS 8: ACF 1] [2009-11-27 12:58:19] [b97b96148b0223bc16666763988dc147]
-   PD            [(Partial) Autocorrelation Function] [Paper: AutoCorrel...] [2009-12-14 09:12:40] [17b3de9cda9f51722106e41c76160a49] [Current]
-                   [(Partial) Autocorrelation Function] [Paper: AutoCorrel...] [2009-12-14 09:23:40] [b97b96148b0223bc16666763988dc147]
-                   [(Partial) Autocorrelation Function] [Paper: AutoCorrel...] [2009-12-14 09:34:01] [b97b96148b0223bc16666763988dc147]
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Dataseries X:
423
427
441
449
452
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




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=67454&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=67454&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67454&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
10.9453387.32260
20.8705556.74330
30.8198396.35040
40.7890126.11170
50.7706545.96950
60.7332025.67940
70.6596065.10932e-06
80.5730164.43862e-05
90.5042013.90550.000121
100.4606253.5680.000357
110.4365963.38190.000636
120.3876573.00280.001948
130.2828022.19060.016189
140.1792451.38840.08507
150.1055370.81750.208442
160.0559180.43310.333234
170.0201020.15570.438391
18-0.03262-0.25270.400694
19-0.105021-0.81350.209577
20-0.185765-1.43890.077684
21-0.240125-1.860.033894
22-0.272188-2.10840.019592
23-0.296834-2.29930.012493
24-0.330595-2.56080.006489
25-0.387777-3.00370.001943
26-0.44256-3.42810.000552
27-0.464409-3.59730.000326
28-0.458644-3.55260.000375
29-0.438967-3.40020.000601
30-0.427925-3.31470.00078
31-0.427286-3.30970.000792
32-0.428072-3.31580.000777
33-0.407572-3.1570.001247
34-0.380073-2.9440.002301
35-0.354323-2.74460.00399
36-0.331756-2.56980.006339

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.945338 & 7.3226 & 0 \tabularnewline
2 & 0.870555 & 6.7433 & 0 \tabularnewline
3 & 0.819839 & 6.3504 & 0 \tabularnewline
4 & 0.789012 & 6.1117 & 0 \tabularnewline
5 & 0.770654 & 5.9695 & 0 \tabularnewline
6 & 0.733202 & 5.6794 & 0 \tabularnewline
7 & 0.659606 & 5.1093 & 2e-06 \tabularnewline
8 & 0.573016 & 4.4386 & 2e-05 \tabularnewline
9 & 0.504201 & 3.9055 & 0.000121 \tabularnewline
10 & 0.460625 & 3.568 & 0.000357 \tabularnewline
11 & 0.436596 & 3.3819 & 0.000636 \tabularnewline
12 & 0.387657 & 3.0028 & 0.001948 \tabularnewline
13 & 0.282802 & 2.1906 & 0.016189 \tabularnewline
14 & 0.179245 & 1.3884 & 0.08507 \tabularnewline
15 & 0.105537 & 0.8175 & 0.208442 \tabularnewline
16 & 0.055918 & 0.4331 & 0.333234 \tabularnewline
17 & 0.020102 & 0.1557 & 0.438391 \tabularnewline
18 & -0.03262 & -0.2527 & 0.400694 \tabularnewline
19 & -0.105021 & -0.8135 & 0.209577 \tabularnewline
20 & -0.185765 & -1.4389 & 0.077684 \tabularnewline
21 & -0.240125 & -1.86 & 0.033894 \tabularnewline
22 & -0.272188 & -2.1084 & 0.019592 \tabularnewline
23 & -0.296834 & -2.2993 & 0.012493 \tabularnewline
24 & -0.330595 & -2.5608 & 0.006489 \tabularnewline
25 & -0.387777 & -3.0037 & 0.001943 \tabularnewline
26 & -0.44256 & -3.4281 & 0.000552 \tabularnewline
27 & -0.464409 & -3.5973 & 0.000326 \tabularnewline
28 & -0.458644 & -3.5526 & 0.000375 \tabularnewline
29 & -0.438967 & -3.4002 & 0.000601 \tabularnewline
30 & -0.427925 & -3.3147 & 0.00078 \tabularnewline
31 & -0.427286 & -3.3097 & 0.000792 \tabularnewline
32 & -0.428072 & -3.3158 & 0.000777 \tabularnewline
33 & -0.407572 & -3.157 & 0.001247 \tabularnewline
34 & -0.380073 & -2.944 & 0.002301 \tabularnewline
35 & -0.354323 & -2.7446 & 0.00399 \tabularnewline
36 & -0.331756 & -2.5698 & 0.006339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67454&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]0.945338[/C][C]7.3226[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.870555[/C][C]6.7433[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.819839[/C][C]6.3504[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.789012[/C][C]6.1117[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.770654[/C][C]5.9695[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.733202[/C][C]5.6794[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.659606[/C][C]5.1093[/C][C]2e-06[/C][/ROW]
[ROW][C]8[/C][C]0.573016[/C][C]4.4386[/C][C]2e-05[/C][/ROW]
[ROW][C]9[/C][C]0.504201[/C][C]3.9055[/C][C]0.000121[/C][/ROW]
[ROW][C]10[/C][C]0.460625[/C][C]3.568[/C][C]0.000357[/C][/ROW]
[ROW][C]11[/C][C]0.436596[/C][C]3.3819[/C][C]0.000636[/C][/ROW]
[ROW][C]12[/C][C]0.387657[/C][C]3.0028[/C][C]0.001948[/C][/ROW]
[ROW][C]13[/C][C]0.282802[/C][C]2.1906[/C][C]0.016189[/C][/ROW]
[ROW][C]14[/C][C]0.179245[/C][C]1.3884[/C][C]0.08507[/C][/ROW]
[ROW][C]15[/C][C]0.105537[/C][C]0.8175[/C][C]0.208442[/C][/ROW]
[ROW][C]16[/C][C]0.055918[/C][C]0.4331[/C][C]0.333234[/C][/ROW]
[ROW][C]17[/C][C]0.020102[/C][C]0.1557[/C][C]0.438391[/C][/ROW]
[ROW][C]18[/C][C]-0.03262[/C][C]-0.2527[/C][C]0.400694[/C][/ROW]
[ROW][C]19[/C][C]-0.105021[/C][C]-0.8135[/C][C]0.209577[/C][/ROW]
[ROW][C]20[/C][C]-0.185765[/C][C]-1.4389[/C][C]0.077684[/C][/ROW]
[ROW][C]21[/C][C]-0.240125[/C][C]-1.86[/C][C]0.033894[/C][/ROW]
[ROW][C]22[/C][C]-0.272188[/C][C]-2.1084[/C][C]0.019592[/C][/ROW]
[ROW][C]23[/C][C]-0.296834[/C][C]-2.2993[/C][C]0.012493[/C][/ROW]
[ROW][C]24[/C][C]-0.330595[/C][C]-2.5608[/C][C]0.006489[/C][/ROW]
[ROW][C]25[/C][C]-0.387777[/C][C]-3.0037[/C][C]0.001943[/C][/ROW]
[ROW][C]26[/C][C]-0.44256[/C][C]-3.4281[/C][C]0.000552[/C][/ROW]
[ROW][C]27[/C][C]-0.464409[/C][C]-3.5973[/C][C]0.000326[/C][/ROW]
[ROW][C]28[/C][C]-0.458644[/C][C]-3.5526[/C][C]0.000375[/C][/ROW]
[ROW][C]29[/C][C]-0.438967[/C][C]-3.4002[/C][C]0.000601[/C][/ROW]
[ROW][C]30[/C][C]-0.427925[/C][C]-3.3147[/C][C]0.00078[/C][/ROW]
[ROW][C]31[/C][C]-0.427286[/C][C]-3.3097[/C][C]0.000792[/C][/ROW]
[ROW][C]32[/C][C]-0.428072[/C][C]-3.3158[/C][C]0.000777[/C][/ROW]
[ROW][C]33[/C][C]-0.407572[/C][C]-3.157[/C][C]0.001247[/C][/ROW]
[ROW][C]34[/C][C]-0.380073[/C][C]-2.944[/C][C]0.002301[/C][/ROW]
[ROW][C]35[/C][C]-0.354323[/C][C]-2.7446[/C][C]0.00399[/C][/ROW]
[ROW][C]36[/C][C]-0.331756[/C][C]-2.5698[/C][C]0.006339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67454&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67454&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
10.9453387.32260
20.8705556.74330
30.8198396.35040
40.7890126.11170
50.7706545.96950
60.7332025.67940
70.6596065.10932e-06
80.5730164.43862e-05
90.5042013.90550.000121
100.4606253.5680.000357
110.4365963.38190.000636
120.3876573.00280.001948
130.2828022.19060.016189
140.1792451.38840.08507
150.1055370.81750.208442
160.0559180.43310.333234
170.0201020.15570.438391
18-0.03262-0.25270.400694
19-0.105021-0.81350.209577
20-0.185765-1.43890.077684
21-0.240125-1.860.033894
22-0.272188-2.10840.019592
23-0.296834-2.29930.012493
24-0.330595-2.56080.006489
25-0.387777-3.00370.001943
26-0.44256-3.42810.000552
27-0.464409-3.59730.000326
28-0.458644-3.55260.000375
29-0.438967-3.40020.000601
30-0.427925-3.31470.00078
31-0.427286-3.30970.000792
32-0.428072-3.31580.000777
33-0.407572-3.1570.001247
34-0.380073-2.9440.002301
35-0.354323-2.74460.00399
36-0.331756-2.56980.006339







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9453387.32260
2-0.217311-1.68330.048759
30.2315771.79380.038943
40.0684910.53050.298853
50.1072230.83050.204761
6-0.198352-1.53640.064845
7-0.255828-1.98160.026054
8-0.125948-0.97560.166593
90.0233380.18080.428576
100.0521580.4040.343821
110.1325111.02640.154405
12-0.217195-1.68240.048846
13-0.413437-3.20250.001091
140.0639350.49520.31112
150.0131990.10220.459454
160.0001330.0010.499591
170.0212830.16490.434804
18-0.037427-0.28990.386442
190.0704450.54570.293659
20-0.169246-1.3110.097431
210.0737370.57120.28501
22-0.159844-1.23810.110242
23-0.052513-0.40680.342816
240.1280320.99170.162656
250.0039090.03030.487972
26-0.091504-0.70880.240602
270.1100880.85270.198599
280.0526320.40770.342477
290.1232570.95470.17177
30-0.002336-0.01810.492811
310.09120.70640.241328
32-0.004487-0.03480.486194
33-0.02131-0.16510.434723
34-0.142634-1.10480.13682
35-0.056315-0.43620.332123
36-0.058484-0.4530.326085

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.945338 & 7.3226 & 0 \tabularnewline
2 & -0.217311 & -1.6833 & 0.048759 \tabularnewline
3 & 0.231577 & 1.7938 & 0.038943 \tabularnewline
4 & 0.068491 & 0.5305 & 0.298853 \tabularnewline
5 & 0.107223 & 0.8305 & 0.204761 \tabularnewline
6 & -0.198352 & -1.5364 & 0.064845 \tabularnewline
7 & -0.255828 & -1.9816 & 0.026054 \tabularnewline
8 & -0.125948 & -0.9756 & 0.166593 \tabularnewline
9 & 0.023338 & 0.1808 & 0.428576 \tabularnewline
10 & 0.052158 & 0.404 & 0.343821 \tabularnewline
11 & 0.132511 & 1.0264 & 0.154405 \tabularnewline
12 & -0.217195 & -1.6824 & 0.048846 \tabularnewline
13 & -0.413437 & -3.2025 & 0.001091 \tabularnewline
14 & 0.063935 & 0.4952 & 0.31112 \tabularnewline
15 & 0.013199 & 0.1022 & 0.459454 \tabularnewline
16 & 0.000133 & 0.001 & 0.499591 \tabularnewline
17 & 0.021283 & 0.1649 & 0.434804 \tabularnewline
18 & -0.037427 & -0.2899 & 0.386442 \tabularnewline
19 & 0.070445 & 0.5457 & 0.293659 \tabularnewline
20 & -0.169246 & -1.311 & 0.097431 \tabularnewline
21 & 0.073737 & 0.5712 & 0.28501 \tabularnewline
22 & -0.159844 & -1.2381 & 0.110242 \tabularnewline
23 & -0.052513 & -0.4068 & 0.342816 \tabularnewline
24 & 0.128032 & 0.9917 & 0.162656 \tabularnewline
25 & 0.003909 & 0.0303 & 0.487972 \tabularnewline
26 & -0.091504 & -0.7088 & 0.240602 \tabularnewline
27 & 0.110088 & 0.8527 & 0.198599 \tabularnewline
28 & 0.052632 & 0.4077 & 0.342477 \tabularnewline
29 & 0.123257 & 0.9547 & 0.17177 \tabularnewline
30 & -0.002336 & -0.0181 & 0.492811 \tabularnewline
31 & 0.0912 & 0.7064 & 0.241328 \tabularnewline
32 & -0.004487 & -0.0348 & 0.486194 \tabularnewline
33 & -0.02131 & -0.1651 & 0.434723 \tabularnewline
34 & -0.142634 & -1.1048 & 0.13682 \tabularnewline
35 & -0.056315 & -0.4362 & 0.332123 \tabularnewline
36 & -0.058484 & -0.453 & 0.326085 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67454&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]0.945338[/C][C]7.3226[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.217311[/C][C]-1.6833[/C][C]0.048759[/C][/ROW]
[ROW][C]3[/C][C]0.231577[/C][C]1.7938[/C][C]0.038943[/C][/ROW]
[ROW][C]4[/C][C]0.068491[/C][C]0.5305[/C][C]0.298853[/C][/ROW]
[ROW][C]5[/C][C]0.107223[/C][C]0.8305[/C][C]0.204761[/C][/ROW]
[ROW][C]6[/C][C]-0.198352[/C][C]-1.5364[/C][C]0.064845[/C][/ROW]
[ROW][C]7[/C][C]-0.255828[/C][C]-1.9816[/C][C]0.026054[/C][/ROW]
[ROW][C]8[/C][C]-0.125948[/C][C]-0.9756[/C][C]0.166593[/C][/ROW]
[ROW][C]9[/C][C]0.023338[/C][C]0.1808[/C][C]0.428576[/C][/ROW]
[ROW][C]10[/C][C]0.052158[/C][C]0.404[/C][C]0.343821[/C][/ROW]
[ROW][C]11[/C][C]0.132511[/C][C]1.0264[/C][C]0.154405[/C][/ROW]
[ROW][C]12[/C][C]-0.217195[/C][C]-1.6824[/C][C]0.048846[/C][/ROW]
[ROW][C]13[/C][C]-0.413437[/C][C]-3.2025[/C][C]0.001091[/C][/ROW]
[ROW][C]14[/C][C]0.063935[/C][C]0.4952[/C][C]0.31112[/C][/ROW]
[ROW][C]15[/C][C]0.013199[/C][C]0.1022[/C][C]0.459454[/C][/ROW]
[ROW][C]16[/C][C]0.000133[/C][C]0.001[/C][C]0.499591[/C][/ROW]
[ROW][C]17[/C][C]0.021283[/C][C]0.1649[/C][C]0.434804[/C][/ROW]
[ROW][C]18[/C][C]-0.037427[/C][C]-0.2899[/C][C]0.386442[/C][/ROW]
[ROW][C]19[/C][C]0.070445[/C][C]0.5457[/C][C]0.293659[/C][/ROW]
[ROW][C]20[/C][C]-0.169246[/C][C]-1.311[/C][C]0.097431[/C][/ROW]
[ROW][C]21[/C][C]0.073737[/C][C]0.5712[/C][C]0.28501[/C][/ROW]
[ROW][C]22[/C][C]-0.159844[/C][C]-1.2381[/C][C]0.110242[/C][/ROW]
[ROW][C]23[/C][C]-0.052513[/C][C]-0.4068[/C][C]0.342816[/C][/ROW]
[ROW][C]24[/C][C]0.128032[/C][C]0.9917[/C][C]0.162656[/C][/ROW]
[ROW][C]25[/C][C]0.003909[/C][C]0.0303[/C][C]0.487972[/C][/ROW]
[ROW][C]26[/C][C]-0.091504[/C][C]-0.7088[/C][C]0.240602[/C][/ROW]
[ROW][C]27[/C][C]0.110088[/C][C]0.8527[/C][C]0.198599[/C][/ROW]
[ROW][C]28[/C][C]0.052632[/C][C]0.4077[/C][C]0.342477[/C][/ROW]
[ROW][C]29[/C][C]0.123257[/C][C]0.9547[/C][C]0.17177[/C][/ROW]
[ROW][C]30[/C][C]-0.002336[/C][C]-0.0181[/C][C]0.492811[/C][/ROW]
[ROW][C]31[/C][C]0.0912[/C][C]0.7064[/C][C]0.241328[/C][/ROW]
[ROW][C]32[/C][C]-0.004487[/C][C]-0.0348[/C][C]0.486194[/C][/ROW]
[ROW][C]33[/C][C]-0.02131[/C][C]-0.1651[/C][C]0.434723[/C][/ROW]
[ROW][C]34[/C][C]-0.142634[/C][C]-1.1048[/C][C]0.13682[/C][/ROW]
[ROW][C]35[/C][C]-0.056315[/C][C]-0.4362[/C][C]0.332123[/C][/ROW]
[ROW][C]36[/C][C]-0.058484[/C][C]-0.453[/C][C]0.326085[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67454&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67454&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
10.9453387.32260
2-0.217311-1.68330.048759
30.2315771.79380.038943
40.0684910.53050.298853
50.1072230.83050.204761
6-0.198352-1.53640.064845
7-0.255828-1.98160.026054
8-0.125948-0.97560.166593
90.0233380.18080.428576
100.0521580.4040.343821
110.1325111.02640.154405
12-0.217195-1.68240.048846
13-0.413437-3.20250.001091
140.0639350.49520.31112
150.0131990.10220.459454
160.0001330.0010.499591
170.0212830.16490.434804
18-0.037427-0.28990.386442
190.0704450.54570.293659
20-0.169246-1.3110.097431
210.0737370.57120.28501
22-0.159844-1.23810.110242
23-0.052513-0.40680.342816
240.1280320.99170.162656
250.0039090.03030.487972
26-0.091504-0.70880.240602
270.1100880.85270.198599
280.0526320.40770.342477
290.1232570.95470.17177
30-0.002336-0.01810.492811
310.09120.70640.241328
32-0.004487-0.03480.486194
33-0.02131-0.16510.434723
34-0.142634-1.10480.13682
35-0.056315-0.43620.332123
36-0.058484-0.4530.326085



Parameters (Session):
par1 = 12 ;
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')