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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 04:46:14 -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/t1261136870kae32mhzr025h9p.htm/, Retrieved Sat, 27 Apr 2024 06:27:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69255, Retrieved Sat, 27 Apr 2024 06:27:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

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] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-18 11:46:14] [2ffc7e281e02b99889abd2ccc65ed6c3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
120.9
119.6
125.9
116.1
107.5
116.7
112.5
113
126.4
114.1
112.5
112.4
113.1
116.3
111.7
118.8
116.5
125.1
113.1
119.6
114.4
114
117.8
117
120.9
115
117.3
119.4
114.9
125.8
117.6
117.6
114.9
121.9
117
106.4
110.5
113.6
114.2
125.4
124.6
120.2
120.8
111.4
124.1
120.2
125.5
116
117
105.7
102
106.4
96.9
107.6
98.8
101.1
105.7
104.6
103.2
101.6

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=69255&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=69255&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69255&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
10.5546814.29653.2e-05
20.5242264.06067.2e-05
30.3592142.78250.003601
40.2396311.85620.034171
50.2671772.06950.021405
60.1668291.29230.100613
70.1952151.51210.067876
8-0.003073-0.02380.490543
9-0.038663-0.29950.382805
10-0.155564-1.2050.116469
11-0.167508-1.29750.099711
12-0.133832-1.03670.152028
13-0.163583-1.26710.105006
14-0.031744-0.24590.403303
150.0091670.0710.471813
160.0277170.21470.415367
170.038270.29640.383959
18-0.066033-0.51150.305442
19-0.06453-0.49980.309506
20-0.052944-0.41010.341595
210.0036710.02840.488703
220.0427240.33090.370923
23-0.029608-0.22930.409693
240.0020610.0160.493657
25-0.094626-0.7330.233216
26-0.134016-1.03810.151698
27-0.067058-0.51940.302686
28-0.126545-0.98020.165458
29-0.043281-0.33530.369302
30-0.144081-1.1160.134426
310.0205690.15930.436973
32-0.063673-0.49320.311833
33-0.126368-0.97880.165795
34-0.106805-0.82730.20567
35-0.216448-1.67660.049412
36-0.074163-0.57450.283901

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.554681 & 4.2965 & 3.2e-05 \tabularnewline
2 & 0.524226 & 4.0606 & 7.2e-05 \tabularnewline
3 & 0.359214 & 2.7825 & 0.003601 \tabularnewline
4 & 0.239631 & 1.8562 & 0.034171 \tabularnewline
5 & 0.267177 & 2.0695 & 0.021405 \tabularnewline
6 & 0.166829 & 1.2923 & 0.100613 \tabularnewline
7 & 0.195215 & 1.5121 & 0.067876 \tabularnewline
8 & -0.003073 & -0.0238 & 0.490543 \tabularnewline
9 & -0.038663 & -0.2995 & 0.382805 \tabularnewline
10 & -0.155564 & -1.205 & 0.116469 \tabularnewline
11 & -0.167508 & -1.2975 & 0.099711 \tabularnewline
12 & -0.133832 & -1.0367 & 0.152028 \tabularnewline
13 & -0.163583 & -1.2671 & 0.105006 \tabularnewline
14 & -0.031744 & -0.2459 & 0.403303 \tabularnewline
15 & 0.009167 & 0.071 & 0.471813 \tabularnewline
16 & 0.027717 & 0.2147 & 0.415367 \tabularnewline
17 & 0.03827 & 0.2964 & 0.383959 \tabularnewline
18 & -0.066033 & -0.5115 & 0.305442 \tabularnewline
19 & -0.06453 & -0.4998 & 0.309506 \tabularnewline
20 & -0.052944 & -0.4101 & 0.341595 \tabularnewline
21 & 0.003671 & 0.0284 & 0.488703 \tabularnewline
22 & 0.042724 & 0.3309 & 0.370923 \tabularnewline
23 & -0.029608 & -0.2293 & 0.409693 \tabularnewline
24 & 0.002061 & 0.016 & 0.493657 \tabularnewline
25 & -0.094626 & -0.733 & 0.233216 \tabularnewline
26 & -0.134016 & -1.0381 & 0.151698 \tabularnewline
27 & -0.067058 & -0.5194 & 0.302686 \tabularnewline
28 & -0.126545 & -0.9802 & 0.165458 \tabularnewline
29 & -0.043281 & -0.3353 & 0.369302 \tabularnewline
30 & -0.144081 & -1.116 & 0.134426 \tabularnewline
31 & 0.020569 & 0.1593 & 0.436973 \tabularnewline
32 & -0.063673 & -0.4932 & 0.311833 \tabularnewline
33 & -0.126368 & -0.9788 & 0.165795 \tabularnewline
34 & -0.106805 & -0.8273 & 0.20567 \tabularnewline
35 & -0.216448 & -1.6766 & 0.049412 \tabularnewline
36 & -0.074163 & -0.5745 & 0.283901 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69255&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]0.554681[/C][C]4.2965[/C][C]3.2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.524226[/C][C]4.0606[/C][C]7.2e-05[/C][/ROW]
[ROW][C]3[/C][C]0.359214[/C][C]2.7825[/C][C]0.003601[/C][/ROW]
[ROW][C]4[/C][C]0.239631[/C][C]1.8562[/C][C]0.034171[/C][/ROW]
[ROW][C]5[/C][C]0.267177[/C][C]2.0695[/C][C]0.021405[/C][/ROW]
[ROW][C]6[/C][C]0.166829[/C][C]1.2923[/C][C]0.100613[/C][/ROW]
[ROW][C]7[/C][C]0.195215[/C][C]1.5121[/C][C]0.067876[/C][/ROW]
[ROW][C]8[/C][C]-0.003073[/C][C]-0.0238[/C][C]0.490543[/C][/ROW]
[ROW][C]9[/C][C]-0.038663[/C][C]-0.2995[/C][C]0.382805[/C][/ROW]
[ROW][C]10[/C][C]-0.155564[/C][C]-1.205[/C][C]0.116469[/C][/ROW]
[ROW][C]11[/C][C]-0.167508[/C][C]-1.2975[/C][C]0.099711[/C][/ROW]
[ROW][C]12[/C][C]-0.133832[/C][C]-1.0367[/C][C]0.152028[/C][/ROW]
[ROW][C]13[/C][C]-0.163583[/C][C]-1.2671[/C][C]0.105006[/C][/ROW]
[ROW][C]14[/C][C]-0.031744[/C][C]-0.2459[/C][C]0.403303[/C][/ROW]
[ROW][C]15[/C][C]0.009167[/C][C]0.071[/C][C]0.471813[/C][/ROW]
[ROW][C]16[/C][C]0.027717[/C][C]0.2147[/C][C]0.415367[/C][/ROW]
[ROW][C]17[/C][C]0.03827[/C][C]0.2964[/C][C]0.383959[/C][/ROW]
[ROW][C]18[/C][C]-0.066033[/C][C]-0.5115[/C][C]0.305442[/C][/ROW]
[ROW][C]19[/C][C]-0.06453[/C][C]-0.4998[/C][C]0.309506[/C][/ROW]
[ROW][C]20[/C][C]-0.052944[/C][C]-0.4101[/C][C]0.341595[/C][/ROW]
[ROW][C]21[/C][C]0.003671[/C][C]0.0284[/C][C]0.488703[/C][/ROW]
[ROW][C]22[/C][C]0.042724[/C][C]0.3309[/C][C]0.370923[/C][/ROW]
[ROW][C]23[/C][C]-0.029608[/C][C]-0.2293[/C][C]0.409693[/C][/ROW]
[ROW][C]24[/C][C]0.002061[/C][C]0.016[/C][C]0.493657[/C][/ROW]
[ROW][C]25[/C][C]-0.094626[/C][C]-0.733[/C][C]0.233216[/C][/ROW]
[ROW][C]26[/C][C]-0.134016[/C][C]-1.0381[/C][C]0.151698[/C][/ROW]
[ROW][C]27[/C][C]-0.067058[/C][C]-0.5194[/C][C]0.302686[/C][/ROW]
[ROW][C]28[/C][C]-0.126545[/C][C]-0.9802[/C][C]0.165458[/C][/ROW]
[ROW][C]29[/C][C]-0.043281[/C][C]-0.3353[/C][C]0.369302[/C][/ROW]
[ROW][C]30[/C][C]-0.144081[/C][C]-1.116[/C][C]0.134426[/C][/ROW]
[ROW][C]31[/C][C]0.020569[/C][C]0.1593[/C][C]0.436973[/C][/ROW]
[ROW][C]32[/C][C]-0.063673[/C][C]-0.4932[/C][C]0.311833[/C][/ROW]
[ROW][C]33[/C][C]-0.126368[/C][C]-0.9788[/C][C]0.165795[/C][/ROW]
[ROW][C]34[/C][C]-0.106805[/C][C]-0.8273[/C][C]0.20567[/C][/ROW]
[ROW][C]35[/C][C]-0.216448[/C][C]-1.6766[/C][C]0.049412[/C][/ROW]
[ROW][C]36[/C][C]-0.074163[/C][C]-0.5745[/C][C]0.283901[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69255&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69255&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
10.5546814.29653.2e-05
20.5242264.06067.2e-05
30.3592142.78250.003601
40.2396311.85620.034171
50.2671772.06950.021405
60.1668291.29230.100613
70.1952151.51210.067876
8-0.003073-0.02380.490543
9-0.038663-0.29950.382805
10-0.155564-1.2050.116469
11-0.167508-1.29750.099711
12-0.133832-1.03670.152028
13-0.163583-1.26710.105006
14-0.031744-0.24590.403303
150.0091670.0710.471813
160.0277170.21470.415367
170.038270.29640.383959
18-0.066033-0.51150.305442
19-0.06453-0.49980.309506
20-0.052944-0.41010.341595
210.0036710.02840.488703
220.0427240.33090.370923
23-0.029608-0.22930.409693
240.0020610.0160.493657
25-0.094626-0.7330.233216
26-0.134016-1.03810.151698
27-0.067058-0.51940.302686
28-0.126545-0.98020.165458
29-0.043281-0.33530.369302
30-0.144081-1.1160.134426
310.0205690.15930.436973
32-0.063673-0.49320.311833
33-0.126368-0.97880.165795
34-0.106805-0.82730.20567
35-0.216448-1.67660.049412
36-0.074163-0.57450.283901






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5546814.29653.2e-05
20.3127912.42290.009217
3-0.022592-0.1750.430835
4-0.089367-0.69220.24573
50.1486861.15170.127003
6-0.024027-0.18610.426492
70.0425010.32920.37157
8-0.248017-1.92110.029735
9-0.072022-0.55790.289501
10-0.109058-0.84480.2008
110.0125790.09740.461353
120.0241850.18730.426016
13-0.014167-0.10970.456492
140.1518951.17660.122007
150.1960911.51890.067018
16-0.012578-0.09740.461355
17-0.030464-0.2360.407128
18-0.213223-1.65160.051918
19-0.107928-0.8360.203233
200.0103580.08020.468159
210.0243480.18860.425522
220.0169920.13160.447863
23-0.093197-0.72190.23658
240.1161280.89950.185985
250.0592730.45910.3239
26-0.112826-0.87390.192817
270.0714820.55370.290923
28-0.11476-0.88890.188796
29-0.008873-0.06870.472718
30-0.164742-1.27610.103422
310.1991191.54240.064121
32-0.06112-0.47340.318812
33-0.161831-1.25350.107437
34-0.022601-0.17510.430807
35-0.018025-0.13960.444713
360.0604970.46860.320525

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.554681 & 4.2965 & 3.2e-05 \tabularnewline
2 & 0.312791 & 2.4229 & 0.009217 \tabularnewline
3 & -0.022592 & -0.175 & 0.430835 \tabularnewline
4 & -0.089367 & -0.6922 & 0.24573 \tabularnewline
5 & 0.148686 & 1.1517 & 0.127003 \tabularnewline
6 & -0.024027 & -0.1861 & 0.426492 \tabularnewline
7 & 0.042501 & 0.3292 & 0.37157 \tabularnewline
8 & -0.248017 & -1.9211 & 0.029735 \tabularnewline
9 & -0.072022 & -0.5579 & 0.289501 \tabularnewline
10 & -0.109058 & -0.8448 & 0.2008 \tabularnewline
11 & 0.012579 & 0.0974 & 0.461353 \tabularnewline
12 & 0.024185 & 0.1873 & 0.426016 \tabularnewline
13 & -0.014167 & -0.1097 & 0.456492 \tabularnewline
14 & 0.151895 & 1.1766 & 0.122007 \tabularnewline
15 & 0.196091 & 1.5189 & 0.067018 \tabularnewline
16 & -0.012578 & -0.0974 & 0.461355 \tabularnewline
17 & -0.030464 & -0.236 & 0.407128 \tabularnewline
18 & -0.213223 & -1.6516 & 0.051918 \tabularnewline
19 & -0.107928 & -0.836 & 0.203233 \tabularnewline
20 & 0.010358 & 0.0802 & 0.468159 \tabularnewline
21 & 0.024348 & 0.1886 & 0.425522 \tabularnewline
22 & 0.016992 & 0.1316 & 0.447863 \tabularnewline
23 & -0.093197 & -0.7219 & 0.23658 \tabularnewline
24 & 0.116128 & 0.8995 & 0.185985 \tabularnewline
25 & 0.059273 & 0.4591 & 0.3239 \tabularnewline
26 & -0.112826 & -0.8739 & 0.192817 \tabularnewline
27 & 0.071482 & 0.5537 & 0.290923 \tabularnewline
28 & -0.11476 & -0.8889 & 0.188796 \tabularnewline
29 & -0.008873 & -0.0687 & 0.472718 \tabularnewline
30 & -0.164742 & -1.2761 & 0.103422 \tabularnewline
31 & 0.199119 & 1.5424 & 0.064121 \tabularnewline
32 & -0.06112 & -0.4734 & 0.318812 \tabularnewline
33 & -0.161831 & -1.2535 & 0.107437 \tabularnewline
34 & -0.022601 & -0.1751 & 0.430807 \tabularnewline
35 & -0.018025 & -0.1396 & 0.444713 \tabularnewline
36 & 0.060497 & 0.4686 & 0.320525 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69255&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]0.554681[/C][C]4.2965[/C][C]3.2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.312791[/C][C]2.4229[/C][C]0.009217[/C][/ROW]
[ROW][C]3[/C][C]-0.022592[/C][C]-0.175[/C][C]0.430835[/C][/ROW]
[ROW][C]4[/C][C]-0.089367[/C][C]-0.6922[/C][C]0.24573[/C][/ROW]
[ROW][C]5[/C][C]0.148686[/C][C]1.1517[/C][C]0.127003[/C][/ROW]
[ROW][C]6[/C][C]-0.024027[/C][C]-0.1861[/C][C]0.426492[/C][/ROW]
[ROW][C]7[/C][C]0.042501[/C][C]0.3292[/C][C]0.37157[/C][/ROW]
[ROW][C]8[/C][C]-0.248017[/C][C]-1.9211[/C][C]0.029735[/C][/ROW]
[ROW][C]9[/C][C]-0.072022[/C][C]-0.5579[/C][C]0.289501[/C][/ROW]
[ROW][C]10[/C][C]-0.109058[/C][C]-0.8448[/C][C]0.2008[/C][/ROW]
[ROW][C]11[/C][C]0.012579[/C][C]0.0974[/C][C]0.461353[/C][/ROW]
[ROW][C]12[/C][C]0.024185[/C][C]0.1873[/C][C]0.426016[/C][/ROW]
[ROW][C]13[/C][C]-0.014167[/C][C]-0.1097[/C][C]0.456492[/C][/ROW]
[ROW][C]14[/C][C]0.151895[/C][C]1.1766[/C][C]0.122007[/C][/ROW]
[ROW][C]15[/C][C]0.196091[/C][C]1.5189[/C][C]0.067018[/C][/ROW]
[ROW][C]16[/C][C]-0.012578[/C][C]-0.0974[/C][C]0.461355[/C][/ROW]
[ROW][C]17[/C][C]-0.030464[/C][C]-0.236[/C][C]0.407128[/C][/ROW]
[ROW][C]18[/C][C]-0.213223[/C][C]-1.6516[/C][C]0.051918[/C][/ROW]
[ROW][C]19[/C][C]-0.107928[/C][C]-0.836[/C][C]0.203233[/C][/ROW]
[ROW][C]20[/C][C]0.010358[/C][C]0.0802[/C][C]0.468159[/C][/ROW]
[ROW][C]21[/C][C]0.024348[/C][C]0.1886[/C][C]0.425522[/C][/ROW]
[ROW][C]22[/C][C]0.016992[/C][C]0.1316[/C][C]0.447863[/C][/ROW]
[ROW][C]23[/C][C]-0.093197[/C][C]-0.7219[/C][C]0.23658[/C][/ROW]
[ROW][C]24[/C][C]0.116128[/C][C]0.8995[/C][C]0.185985[/C][/ROW]
[ROW][C]25[/C][C]0.059273[/C][C]0.4591[/C][C]0.3239[/C][/ROW]
[ROW][C]26[/C][C]-0.112826[/C][C]-0.8739[/C][C]0.192817[/C][/ROW]
[ROW][C]27[/C][C]0.071482[/C][C]0.5537[/C][C]0.290923[/C][/ROW]
[ROW][C]28[/C][C]-0.11476[/C][C]-0.8889[/C][C]0.188796[/C][/ROW]
[ROW][C]29[/C][C]-0.008873[/C][C]-0.0687[/C][C]0.472718[/C][/ROW]
[ROW][C]30[/C][C]-0.164742[/C][C]-1.2761[/C][C]0.103422[/C][/ROW]
[ROW][C]31[/C][C]0.199119[/C][C]1.5424[/C][C]0.064121[/C][/ROW]
[ROW][C]32[/C][C]-0.06112[/C][C]-0.4734[/C][C]0.318812[/C][/ROW]
[ROW][C]33[/C][C]-0.161831[/C][C]-1.2535[/C][C]0.107437[/C][/ROW]
[ROW][C]34[/C][C]-0.022601[/C][C]-0.1751[/C][C]0.430807[/C][/ROW]
[ROW][C]35[/C][C]-0.018025[/C][C]-0.1396[/C][C]0.444713[/C][/ROW]
[ROW][C]36[/C][C]0.060497[/C][C]0.4686[/C][C]0.320525[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69255&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69255&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
10.5546814.29653.2e-05
20.3127912.42290.009217
3-0.022592-0.1750.430835
4-0.089367-0.69220.24573
50.1486861.15170.127003
6-0.024027-0.18610.426492
70.0425010.32920.37157
8-0.248017-1.92110.029735
9-0.072022-0.55790.289501
10-0.109058-0.84480.2008
110.0125790.09740.461353
120.0241850.18730.426016
13-0.014167-0.10970.456492
140.1518951.17660.122007
150.1960911.51890.067018
16-0.012578-0.09740.461355
17-0.030464-0.2360.407128
18-0.213223-1.65160.051918
19-0.107928-0.8360.203233
200.0103580.08020.468159
210.0243480.18860.425522
220.0169920.13160.447863
23-0.093197-0.72190.23658
240.1161280.89950.185985
250.0592730.45910.3239
26-0.112826-0.87390.192817
270.0714820.55370.290923
28-0.11476-0.88890.188796
29-0.008873-0.06870.472718
30-0.164742-1.27610.103422
310.1991191.54240.064121
32-0.06112-0.47340.318812
33-0.161831-1.25350.107437
34-0.022601-0.17510.430807
35-0.018025-0.13960.444713
360.0604970.46860.320525


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')