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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, 27 Nov 2009 05:46:16 -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/t1259326112818v41kqykfu0aw.htm/, Retrieved Sun, 28 Apr 2024 23:15:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60670, Retrieved Sun, 28 Apr 2024 23:15:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

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] [Workshop 8] [2009-11-27 12:46:16] [0bdf648420800d03e6dbfbd39fe2311c] [Current]
-   P             [(Partial) Autocorrelation Function] [Workshop 8] [2009-11-27 13:00:12] [dc3c82a565f0b2cd85906905748a1f2c]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
62
64
62
64
64
69
69
65
56
58
53
62
55
60
59
58
53
57
57
53
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53
57
57
55
49
50
49
54
58
58
52
56
52
59
53
52
53
51
50
56
52
46
48
46
48
48
49
53
48
51
48
50
55
52
53
52
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53
56
54
52
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54
59
56
56
51
53
52
51
46
49
46
55
57
53
52
53
50
54
53
50
51
52
47
51
49
53
52
45
53
51
48
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40
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36
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46
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36
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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=60670&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=60670&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60670&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
10.6128156.3980
20.5576985.82250
30.3991154.16693.1e-05
40.3147273.28580.000684
50.2722312.84220.002675
60.2391952.49730.007005
70.1507261.57360.059236
80.1294151.35110.089725
90.044540.4650.321425
10-0.000262-0.00270.498912
11-0.106364-1.11050.13462
12-0.276748-2.88930.002329
13-0.237252-2.4770.007393
14-0.223706-2.33560.010672
15-0.215054-2.24520.013386
16-0.135078-1.41030.080656
17-0.1388-1.44910.075088
18-0.146769-1.53230.064171
19-0.095059-0.99240.16159
20-0.10541-1.10050.136766
21-0.077597-0.81010.209813
22-0.054069-0.56450.286788
230.0417510.43590.331889
240.0334580.34930.363763
250.1274591.33070.09303
260.2010792.09930.019048
270.2081492.17310.015967
280.2023622.11270.018454
290.1439681.50310.067856
300.1053541.09990.136894
310.0645550.6740.250877
320.0273120.28510.388039
330.023470.2450.403444
34-0.066657-0.69590.243979
35-0.108023-1.12780.130942
36-0.144338-1.50690.067361

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.612815 & 6.398 & 0 \tabularnewline
2 & 0.557698 & 5.8225 & 0 \tabularnewline
3 & 0.399115 & 4.1669 & 3.1e-05 \tabularnewline
4 & 0.314727 & 3.2858 & 0.000684 \tabularnewline
5 & 0.272231 & 2.8422 & 0.002675 \tabularnewline
6 & 0.239195 & 2.4973 & 0.007005 \tabularnewline
7 & 0.150726 & 1.5736 & 0.059236 \tabularnewline
8 & 0.129415 & 1.3511 & 0.089725 \tabularnewline
9 & 0.04454 & 0.465 & 0.321425 \tabularnewline
10 & -0.000262 & -0.0027 & 0.498912 \tabularnewline
11 & -0.106364 & -1.1105 & 0.13462 \tabularnewline
12 & -0.276748 & -2.8893 & 0.002329 \tabularnewline
13 & -0.237252 & -2.477 & 0.007393 \tabularnewline
14 & -0.223706 & -2.3356 & 0.010672 \tabularnewline
15 & -0.215054 & -2.2452 & 0.013386 \tabularnewline
16 & -0.135078 & -1.4103 & 0.080656 \tabularnewline
17 & -0.1388 & -1.4491 & 0.075088 \tabularnewline
18 & -0.146769 & -1.5323 & 0.064171 \tabularnewline
19 & -0.095059 & -0.9924 & 0.16159 \tabularnewline
20 & -0.10541 & -1.1005 & 0.136766 \tabularnewline
21 & -0.077597 & -0.8101 & 0.209813 \tabularnewline
22 & -0.054069 & -0.5645 & 0.286788 \tabularnewline
23 & 0.041751 & 0.4359 & 0.331889 \tabularnewline
24 & 0.033458 & 0.3493 & 0.363763 \tabularnewline
25 & 0.127459 & 1.3307 & 0.09303 \tabularnewline
26 & 0.201079 & 2.0993 & 0.019048 \tabularnewline
27 & 0.208149 & 2.1731 & 0.015967 \tabularnewline
28 & 0.202362 & 2.1127 & 0.018454 \tabularnewline
29 & 0.143968 & 1.5031 & 0.067856 \tabularnewline
30 & 0.105354 & 1.0999 & 0.136894 \tabularnewline
31 & 0.064555 & 0.674 & 0.250877 \tabularnewline
32 & 0.027312 & 0.2851 & 0.388039 \tabularnewline
33 & 0.02347 & 0.245 & 0.403444 \tabularnewline
34 & -0.066657 & -0.6959 & 0.243979 \tabularnewline
35 & -0.108023 & -1.1278 & 0.130942 \tabularnewline
36 & -0.144338 & -1.5069 & 0.067361 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60670&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]0.612815[/C][C]6.398[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.557698[/C][C]5.8225[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.399115[/C][C]4.1669[/C][C]3.1e-05[/C][/ROW]
[ROW][C]4[/C][C]0.314727[/C][C]3.2858[/C][C]0.000684[/C][/ROW]
[ROW][C]5[/C][C]0.272231[/C][C]2.8422[/C][C]0.002675[/C][/ROW]
[ROW][C]6[/C][C]0.239195[/C][C]2.4973[/C][C]0.007005[/C][/ROW]
[ROW][C]7[/C][C]0.150726[/C][C]1.5736[/C][C]0.059236[/C][/ROW]
[ROW][C]8[/C][C]0.129415[/C][C]1.3511[/C][C]0.089725[/C][/ROW]
[ROW][C]9[/C][C]0.04454[/C][C]0.465[/C][C]0.321425[/C][/ROW]
[ROW][C]10[/C][C]-0.000262[/C][C]-0.0027[/C][C]0.498912[/C][/ROW]
[ROW][C]11[/C][C]-0.106364[/C][C]-1.1105[/C][C]0.13462[/C][/ROW]
[ROW][C]12[/C][C]-0.276748[/C][C]-2.8893[/C][C]0.002329[/C][/ROW]
[ROW][C]13[/C][C]-0.237252[/C][C]-2.477[/C][C]0.007393[/C][/ROW]
[ROW][C]14[/C][C]-0.223706[/C][C]-2.3356[/C][C]0.010672[/C][/ROW]
[ROW][C]15[/C][C]-0.215054[/C][C]-2.2452[/C][C]0.013386[/C][/ROW]
[ROW][C]16[/C][C]-0.135078[/C][C]-1.4103[/C][C]0.080656[/C][/ROW]
[ROW][C]17[/C][C]-0.1388[/C][C]-1.4491[/C][C]0.075088[/C][/ROW]
[ROW][C]18[/C][C]-0.146769[/C][C]-1.5323[/C][C]0.064171[/C][/ROW]
[ROW][C]19[/C][C]-0.095059[/C][C]-0.9924[/C][C]0.16159[/C][/ROW]
[ROW][C]20[/C][C]-0.10541[/C][C]-1.1005[/C][C]0.136766[/C][/ROW]
[ROW][C]21[/C][C]-0.077597[/C][C]-0.8101[/C][C]0.209813[/C][/ROW]
[ROW][C]22[/C][C]-0.054069[/C][C]-0.5645[/C][C]0.286788[/C][/ROW]
[ROW][C]23[/C][C]0.041751[/C][C]0.4359[/C][C]0.331889[/C][/ROW]
[ROW][C]24[/C][C]0.033458[/C][C]0.3493[/C][C]0.363763[/C][/ROW]
[ROW][C]25[/C][C]0.127459[/C][C]1.3307[/C][C]0.09303[/C][/ROW]
[ROW][C]26[/C][C]0.201079[/C][C]2.0993[/C][C]0.019048[/C][/ROW]
[ROW][C]27[/C][C]0.208149[/C][C]2.1731[/C][C]0.015967[/C][/ROW]
[ROW][C]28[/C][C]0.202362[/C][C]2.1127[/C][C]0.018454[/C][/ROW]
[ROW][C]29[/C][C]0.143968[/C][C]1.5031[/C][C]0.067856[/C][/ROW]
[ROW][C]30[/C][C]0.105354[/C][C]1.0999[/C][C]0.136894[/C][/ROW]
[ROW][C]31[/C][C]0.064555[/C][C]0.674[/C][C]0.250877[/C][/ROW]
[ROW][C]32[/C][C]0.027312[/C][C]0.2851[/C][C]0.388039[/C][/ROW]
[ROW][C]33[/C][C]0.02347[/C][C]0.245[/C][C]0.403444[/C][/ROW]
[ROW][C]34[/C][C]-0.066657[/C][C]-0.6959[/C][C]0.243979[/C][/ROW]
[ROW][C]35[/C][C]-0.108023[/C][C]-1.1278[/C][C]0.130942[/C][/ROW]
[ROW][C]36[/C][C]-0.144338[/C][C]-1.5069[/C][C]0.067361[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60670&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60670&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
10.6128156.3980
20.5576985.82250
30.3991154.16693.1e-05
40.3147273.28580.000684
50.2722312.84220.002675
60.2391952.49730.007005
70.1507261.57360.059236
80.1294151.35110.089725
90.044540.4650.321425
10-0.000262-0.00270.498912
11-0.106364-1.11050.13462
12-0.276748-2.88930.002329
13-0.237252-2.4770.007393
14-0.223706-2.33560.010672
15-0.215054-2.24520.013386
16-0.135078-1.41030.080656
17-0.1388-1.44910.075088
18-0.146769-1.53230.064171
19-0.095059-0.99240.16159
20-0.10541-1.10050.136766
21-0.077597-0.81010.209813
22-0.054069-0.56450.286788
230.0417510.43590.331889
240.0334580.34930.363763
250.1274591.33070.09303
260.2010792.09930.019048
270.2081492.17310.015967
280.2023622.11270.018454
290.1439681.50310.067856
300.1053541.09990.136894
310.0645550.6740.250877
320.0273120.28510.388039
330.023470.2450.403444
34-0.066657-0.69590.243979
35-0.108023-1.12780.130942
36-0.144338-1.50690.067361






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6128156.3980
20.2917023.04550.001457
3-0.03801-0.39680.346133
4-0.020204-0.21090.416665
50.0621550.64890.258879
60.0463280.48370.314793
7-0.095087-0.99270.161517
80.0008490.00890.496473
9-0.064602-0.67450.250721
10-0.056253-0.58730.279108
11-0.148026-1.54540.062569
12-0.29493-3.07920.001313
130.0880860.91960.179894
140.1253861.30910.096632
15-0.044082-0.46020.323134
160.0777690.81190.209299
170.0491520.51320.304437
18-0.039087-0.40810.342006
190.0419050.43750.331308
20-0.002924-0.03050.487849
21-0.015357-0.16030.436458
220.0200430.20930.417321
230.1168991.22050.112462
24-0.169313-1.76770.039957
250.1034391.07990.141279
260.2401842.50760.006815
27-0.063887-0.6670.253092
28-0.015921-0.16620.434145
29-0.075829-0.79170.215133
30-0.099206-1.03570.151309
31-0.034244-0.35750.360698
32-0.080725-0.84280.200595
33-0.068214-0.71220.238939
34-0.113172-1.18160.119977
350.0079160.08260.467141
36-0.13177-1.37570.085865

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.612815 & 6.398 & 0 \tabularnewline
2 & 0.291702 & 3.0455 & 0.001457 \tabularnewline
3 & -0.03801 & -0.3968 & 0.346133 \tabularnewline
4 & -0.020204 & -0.2109 & 0.416665 \tabularnewline
5 & 0.062155 & 0.6489 & 0.258879 \tabularnewline
6 & 0.046328 & 0.4837 & 0.314793 \tabularnewline
7 & -0.095087 & -0.9927 & 0.161517 \tabularnewline
8 & 0.000849 & 0.0089 & 0.496473 \tabularnewline
9 & -0.064602 & -0.6745 & 0.250721 \tabularnewline
10 & -0.056253 & -0.5873 & 0.279108 \tabularnewline
11 & -0.148026 & -1.5454 & 0.062569 \tabularnewline
12 & -0.29493 & -3.0792 & 0.001313 \tabularnewline
13 & 0.088086 & 0.9196 & 0.179894 \tabularnewline
14 & 0.125386 & 1.3091 & 0.096632 \tabularnewline
15 & -0.044082 & -0.4602 & 0.323134 \tabularnewline
16 & 0.077769 & 0.8119 & 0.209299 \tabularnewline
17 & 0.049152 & 0.5132 & 0.304437 \tabularnewline
18 & -0.039087 & -0.4081 & 0.342006 \tabularnewline
19 & 0.041905 & 0.4375 & 0.331308 \tabularnewline
20 & -0.002924 & -0.0305 & 0.487849 \tabularnewline
21 & -0.015357 & -0.1603 & 0.436458 \tabularnewline
22 & 0.020043 & 0.2093 & 0.417321 \tabularnewline
23 & 0.116899 & 1.2205 & 0.112462 \tabularnewline
24 & -0.169313 & -1.7677 & 0.039957 \tabularnewline
25 & 0.103439 & 1.0799 & 0.141279 \tabularnewline
26 & 0.240184 & 2.5076 & 0.006815 \tabularnewline
27 & -0.063887 & -0.667 & 0.253092 \tabularnewline
28 & -0.015921 & -0.1662 & 0.434145 \tabularnewline
29 & -0.075829 & -0.7917 & 0.215133 \tabularnewline
30 & -0.099206 & -1.0357 & 0.151309 \tabularnewline
31 & -0.034244 & -0.3575 & 0.360698 \tabularnewline
32 & -0.080725 & -0.8428 & 0.200595 \tabularnewline
33 & -0.068214 & -0.7122 & 0.238939 \tabularnewline
34 & -0.113172 & -1.1816 & 0.119977 \tabularnewline
35 & 0.007916 & 0.0826 & 0.467141 \tabularnewline
36 & -0.13177 & -1.3757 & 0.085865 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60670&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]0.612815[/C][C]6.398[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.291702[/C][C]3.0455[/C][C]0.001457[/C][/ROW]
[ROW][C]3[/C][C]-0.03801[/C][C]-0.3968[/C][C]0.346133[/C][/ROW]
[ROW][C]4[/C][C]-0.020204[/C][C]-0.2109[/C][C]0.416665[/C][/ROW]
[ROW][C]5[/C][C]0.062155[/C][C]0.6489[/C][C]0.258879[/C][/ROW]
[ROW][C]6[/C][C]0.046328[/C][C]0.4837[/C][C]0.314793[/C][/ROW]
[ROW][C]7[/C][C]-0.095087[/C][C]-0.9927[/C][C]0.161517[/C][/ROW]
[ROW][C]8[/C][C]0.000849[/C][C]0.0089[/C][C]0.496473[/C][/ROW]
[ROW][C]9[/C][C]-0.064602[/C][C]-0.6745[/C][C]0.250721[/C][/ROW]
[ROW][C]10[/C][C]-0.056253[/C][C]-0.5873[/C][C]0.279108[/C][/ROW]
[ROW][C]11[/C][C]-0.148026[/C][C]-1.5454[/C][C]0.062569[/C][/ROW]
[ROW][C]12[/C][C]-0.29493[/C][C]-3.0792[/C][C]0.001313[/C][/ROW]
[ROW][C]13[/C][C]0.088086[/C][C]0.9196[/C][C]0.179894[/C][/ROW]
[ROW][C]14[/C][C]0.125386[/C][C]1.3091[/C][C]0.096632[/C][/ROW]
[ROW][C]15[/C][C]-0.044082[/C][C]-0.4602[/C][C]0.323134[/C][/ROW]
[ROW][C]16[/C][C]0.077769[/C][C]0.8119[/C][C]0.209299[/C][/ROW]
[ROW][C]17[/C][C]0.049152[/C][C]0.5132[/C][C]0.304437[/C][/ROW]
[ROW][C]18[/C][C]-0.039087[/C][C]-0.4081[/C][C]0.342006[/C][/ROW]
[ROW][C]19[/C][C]0.041905[/C][C]0.4375[/C][C]0.331308[/C][/ROW]
[ROW][C]20[/C][C]-0.002924[/C][C]-0.0305[/C][C]0.487849[/C][/ROW]
[ROW][C]21[/C][C]-0.015357[/C][C]-0.1603[/C][C]0.436458[/C][/ROW]
[ROW][C]22[/C][C]0.020043[/C][C]0.2093[/C][C]0.417321[/C][/ROW]
[ROW][C]23[/C][C]0.116899[/C][C]1.2205[/C][C]0.112462[/C][/ROW]
[ROW][C]24[/C][C]-0.169313[/C][C]-1.7677[/C][C]0.039957[/C][/ROW]
[ROW][C]25[/C][C]0.103439[/C][C]1.0799[/C][C]0.141279[/C][/ROW]
[ROW][C]26[/C][C]0.240184[/C][C]2.5076[/C][C]0.006815[/C][/ROW]
[ROW][C]27[/C][C]-0.063887[/C][C]-0.667[/C][C]0.253092[/C][/ROW]
[ROW][C]28[/C][C]-0.015921[/C][C]-0.1662[/C][C]0.434145[/C][/ROW]
[ROW][C]29[/C][C]-0.075829[/C][C]-0.7917[/C][C]0.215133[/C][/ROW]
[ROW][C]30[/C][C]-0.099206[/C][C]-1.0357[/C][C]0.151309[/C][/ROW]
[ROW][C]31[/C][C]-0.034244[/C][C]-0.3575[/C][C]0.360698[/C][/ROW]
[ROW][C]32[/C][C]-0.080725[/C][C]-0.8428[/C][C]0.200595[/C][/ROW]
[ROW][C]33[/C][C]-0.068214[/C][C]-0.7122[/C][C]0.238939[/C][/ROW]
[ROW][C]34[/C][C]-0.113172[/C][C]-1.1816[/C][C]0.119977[/C][/ROW]
[ROW][C]35[/C][C]0.007916[/C][C]0.0826[/C][C]0.467141[/C][/ROW]
[ROW][C]36[/C][C]-0.13177[/C][C]-1.3757[/C][C]0.085865[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60670&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60670&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
10.6128156.3980
20.2917023.04550.001457
3-0.03801-0.39680.346133
4-0.020204-0.21090.416665
50.0621550.64890.258879
60.0463280.48370.314793
7-0.095087-0.99270.161517
80.0008490.00890.496473
9-0.064602-0.67450.250721
10-0.056253-0.58730.279108
11-0.148026-1.54540.062569
12-0.29493-3.07920.001313
130.0880860.91960.179894
140.1253861.30910.096632
15-0.044082-0.46020.323134
160.0777690.81190.209299
170.0491520.51320.304437
18-0.039087-0.40810.342006
190.0419050.43750.331308
20-0.002924-0.03050.487849
21-0.015357-0.16030.436458
220.0200430.20930.417321
230.1168991.22050.112462
24-0.169313-1.76770.039957
250.1034391.07990.141279
260.2401842.50760.006815
27-0.063887-0.6670.253092
28-0.015921-0.16620.434145
29-0.075829-0.79170.215133
30-0.099206-1.03570.151309
31-0.034244-0.35750.360698
32-0.080725-0.84280.200595
33-0.068214-0.71220.238939
34-0.113172-1.18160.119977
350.0079160.08260.467141
36-0.13177-1.37570.085865


Figures (Output of Computation)

Input Parameters & R Code

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