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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 computationThu, 03 Dec 2009 11:57:52 -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/t12598667425x12pkrxfcrml6t.htm/, Retrieved Thu, 28 Mar 2024 10:24:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63067, Retrieved Thu, 28 Mar 2024 10:24:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-   PD      [(Partial) Autocorrelation Function] [WS 9 (P)ACF 2] [2009-12-03 18:57:52] [eba9f01697e64705b70041e6f338cb22] [Current]
-   PD        [(Partial) Autocorrelation Function] [WS 9 (P)ACF 2] [2009-12-03 19:09:40] [83058a88a37d754675a5cd22dab372fc]
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Dataseries X:
106,9
107,5
116,1
102
111,2
111,8
91,2
93
105,4
111,6
104,6
91,6
98,3
97,7
106,3
102,3
106,6
108,1
93,8
88,2
108,9
114,2
102,5
94,2
97,4
98,5
106,5
102,9
97,1
103,7
93,4
85,8
108,6
110,2
101,2
101,2
96,9
99,4
118,7
108
101,2
119,9
94,8
95,3
118
115,9
111,4
108,2
108,8
109,5
124,8
115,3
109,5
124,2
92,9
98,4
120,9
111,7
116,1
109,4
111,7
114,3
133,7
114,3
126,5
131
104
108,9
128,5
132,4
128
116,4
120,9
118,6
133,1
121,1
127,6
135,4
114,9
114,3
128,9
138,9
129,4
115
128
127
128,8
137,9
128,4
135,9
122,2
113,1
136,2
138
115,2
111




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=63067&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=63067&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63067&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3862223.53980.000328
20.4125593.78120.000146
30.5204224.76974e-06
40.1850231.69580.046817
50.2861892.6230.005175
60.2617432.39890.009329
70.0285070.26130.397263
80.1186981.08790.139879
90.1415951.29770.098964
10-0.048776-0.4470.328
110.0553540.50730.306627
120.0695230.63720.262866
13-0.06588-0.60380.273802
140.0938010.85970.196199
150.062940.57690.282791
16-0.037566-0.34430.365742
170.1023060.93770.175556
180.1165431.06810.144259
19-0.037951-0.34780.364421
200.1407491.290.100297
210.1141741.04640.149184
22-0.124965-1.14530.127664
230.1672161.53260.064571
24-0.115425-1.05790.146571
25-0.103842-0.95170.171982
260.0615810.56440.286993
27-0.139942-1.28260.101581
28-0.063059-0.57790.282423
29-0.026874-0.24630.403024
30-0.160494-1.4710.07252
31-0.0798-0.73140.233291
32-0.072887-0.6680.252975
33-0.213805-1.95960.026682
34-0.115066-1.05460.147317
35-0.118713-1.0880.139849
36-0.224317-2.05590.021449

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.386222 & 3.5398 & 0.000328 \tabularnewline
2 & 0.412559 & 3.7812 & 0.000146 \tabularnewline
3 & 0.520422 & 4.7697 & 4e-06 \tabularnewline
4 & 0.185023 & 1.6958 & 0.046817 \tabularnewline
5 & 0.286189 & 2.623 & 0.005175 \tabularnewline
6 & 0.261743 & 2.3989 & 0.009329 \tabularnewline
7 & 0.028507 & 0.2613 & 0.397263 \tabularnewline
8 & 0.118698 & 1.0879 & 0.139879 \tabularnewline
9 & 0.141595 & 1.2977 & 0.098964 \tabularnewline
10 & -0.048776 & -0.447 & 0.328 \tabularnewline
11 & 0.055354 & 0.5073 & 0.306627 \tabularnewline
12 & 0.069523 & 0.6372 & 0.262866 \tabularnewline
13 & -0.06588 & -0.6038 & 0.273802 \tabularnewline
14 & 0.093801 & 0.8597 & 0.196199 \tabularnewline
15 & 0.06294 & 0.5769 & 0.282791 \tabularnewline
16 & -0.037566 & -0.3443 & 0.365742 \tabularnewline
17 & 0.102306 & 0.9377 & 0.175556 \tabularnewline
18 & 0.116543 & 1.0681 & 0.144259 \tabularnewline
19 & -0.037951 & -0.3478 & 0.364421 \tabularnewline
20 & 0.140749 & 1.29 & 0.100297 \tabularnewline
21 & 0.114174 & 1.0464 & 0.149184 \tabularnewline
22 & -0.124965 & -1.1453 & 0.127664 \tabularnewline
23 & 0.167216 & 1.5326 & 0.064571 \tabularnewline
24 & -0.115425 & -1.0579 & 0.146571 \tabularnewline
25 & -0.103842 & -0.9517 & 0.171982 \tabularnewline
26 & 0.061581 & 0.5644 & 0.286993 \tabularnewline
27 & -0.139942 & -1.2826 & 0.101581 \tabularnewline
28 & -0.063059 & -0.5779 & 0.282423 \tabularnewline
29 & -0.026874 & -0.2463 & 0.403024 \tabularnewline
30 & -0.160494 & -1.471 & 0.07252 \tabularnewline
31 & -0.0798 & -0.7314 & 0.233291 \tabularnewline
32 & -0.072887 & -0.668 & 0.252975 \tabularnewline
33 & -0.213805 & -1.9596 & 0.026682 \tabularnewline
34 & -0.115066 & -1.0546 & 0.147317 \tabularnewline
35 & -0.118713 & -1.088 & 0.139849 \tabularnewline
36 & -0.224317 & -2.0559 & 0.021449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63067&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]0.386222[/C][C]3.5398[/C][C]0.000328[/C][/ROW]
[ROW][C]2[/C][C]0.412559[/C][C]3.7812[/C][C]0.000146[/C][/ROW]
[ROW][C]3[/C][C]0.520422[/C][C]4.7697[/C][C]4e-06[/C][/ROW]
[ROW][C]4[/C][C]0.185023[/C][C]1.6958[/C][C]0.046817[/C][/ROW]
[ROW][C]5[/C][C]0.286189[/C][C]2.623[/C][C]0.005175[/C][/ROW]
[ROW][C]6[/C][C]0.261743[/C][C]2.3989[/C][C]0.009329[/C][/ROW]
[ROW][C]7[/C][C]0.028507[/C][C]0.2613[/C][C]0.397263[/C][/ROW]
[ROW][C]8[/C][C]0.118698[/C][C]1.0879[/C][C]0.139879[/C][/ROW]
[ROW][C]9[/C][C]0.141595[/C][C]1.2977[/C][C]0.098964[/C][/ROW]
[ROW][C]10[/C][C]-0.048776[/C][C]-0.447[/C][C]0.328[/C][/ROW]
[ROW][C]11[/C][C]0.055354[/C][C]0.5073[/C][C]0.306627[/C][/ROW]
[ROW][C]12[/C][C]0.069523[/C][C]0.6372[/C][C]0.262866[/C][/ROW]
[ROW][C]13[/C][C]-0.06588[/C][C]-0.6038[/C][C]0.273802[/C][/ROW]
[ROW][C]14[/C][C]0.093801[/C][C]0.8597[/C][C]0.196199[/C][/ROW]
[ROW][C]15[/C][C]0.06294[/C][C]0.5769[/C][C]0.282791[/C][/ROW]
[ROW][C]16[/C][C]-0.037566[/C][C]-0.3443[/C][C]0.365742[/C][/ROW]
[ROW][C]17[/C][C]0.102306[/C][C]0.9377[/C][C]0.175556[/C][/ROW]
[ROW][C]18[/C][C]0.116543[/C][C]1.0681[/C][C]0.144259[/C][/ROW]
[ROW][C]19[/C][C]-0.037951[/C][C]-0.3478[/C][C]0.364421[/C][/ROW]
[ROW][C]20[/C][C]0.140749[/C][C]1.29[/C][C]0.100297[/C][/ROW]
[ROW][C]21[/C][C]0.114174[/C][C]1.0464[/C][C]0.149184[/C][/ROW]
[ROW][C]22[/C][C]-0.124965[/C][C]-1.1453[/C][C]0.127664[/C][/ROW]
[ROW][C]23[/C][C]0.167216[/C][C]1.5326[/C][C]0.064571[/C][/ROW]
[ROW][C]24[/C][C]-0.115425[/C][C]-1.0579[/C][C]0.146571[/C][/ROW]
[ROW][C]25[/C][C]-0.103842[/C][C]-0.9517[/C][C]0.171982[/C][/ROW]
[ROW][C]26[/C][C]0.061581[/C][C]0.5644[/C][C]0.286993[/C][/ROW]
[ROW][C]27[/C][C]-0.139942[/C][C]-1.2826[/C][C]0.101581[/C][/ROW]
[ROW][C]28[/C][C]-0.063059[/C][C]-0.5779[/C][C]0.282423[/C][/ROW]
[ROW][C]29[/C][C]-0.026874[/C][C]-0.2463[/C][C]0.403024[/C][/ROW]
[ROW][C]30[/C][C]-0.160494[/C][C]-1.471[/C][C]0.07252[/C][/ROW]
[ROW][C]31[/C][C]-0.0798[/C][C]-0.7314[/C][C]0.233291[/C][/ROW]
[ROW][C]32[/C][C]-0.072887[/C][C]-0.668[/C][C]0.252975[/C][/ROW]
[ROW][C]33[/C][C]-0.213805[/C][C]-1.9596[/C][C]0.026682[/C][/ROW]
[ROW][C]34[/C][C]-0.115066[/C][C]-1.0546[/C][C]0.147317[/C][/ROW]
[ROW][C]35[/C][C]-0.118713[/C][C]-1.088[/C][C]0.139849[/C][/ROW]
[ROW][C]36[/C][C]-0.224317[/C][C]-2.0559[/C][C]0.021449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63067&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63067&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
10.3862223.53980.000328
20.4125593.78120.000146
30.5204224.76974e-06
40.1850231.69580.046817
50.2861892.6230.005175
60.2617432.39890.009329
70.0285070.26130.397263
80.1186981.08790.139879
90.1415951.29770.098964
10-0.048776-0.4470.328
110.0553540.50730.306627
120.0695230.63720.262866
13-0.06588-0.60380.273802
140.0938010.85970.196199
150.062940.57690.282791
16-0.037566-0.34430.365742
170.1023060.93770.175556
180.1165431.06810.144259
19-0.037951-0.34780.364421
200.1407491.290.100297
210.1141741.04640.149184
22-0.124965-1.14530.127664
230.1672161.53260.064571
24-0.115425-1.05790.146571
25-0.103842-0.95170.171982
260.0615810.56440.286993
27-0.139942-1.28260.101581
28-0.063059-0.57790.282423
29-0.026874-0.24630.403024
30-0.160494-1.4710.07252
31-0.0798-0.73140.233291
32-0.072887-0.6680.252975
33-0.213805-1.95960.026682
34-0.115066-1.05460.147317
35-0.118713-1.0880.139849
36-0.224317-2.05590.021449







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3862223.53980.000328
20.3095692.83720.002851
30.3780693.46510.000419
4-0.189563-1.73740.042993
50.03390.31070.3784
60.0224440.20570.418762
7-0.136349-1.24970.107448
8-0.045883-0.42050.337588
90.1270811.16470.123716
10-0.077012-0.70580.241125
11-0.020138-0.18460.427005
120.0684510.62740.26606
13-0.020759-0.19030.424783
140.0584360.53560.296835
150.0418720.38380.351062
16-0.032638-0.29910.382788
170.0028990.02660.489434
180.1318321.20830.115169
19-0.117589-1.07770.142122
200.0469860.43060.333919
210.0828220.75910.224965
22-0.238028-2.18160.015968
230.116861.0710.14361
24-0.220718-2.02290.023131
250.0820890.75240.226968
26-0.023048-0.21120.416607
270.0582660.5340.29737
280.0050090.04590.481747
29-0.078627-0.72060.23657
30-0.034698-0.3180.375631
310.0026830.02460.49022
32-0.086215-0.79020.215827
33-0.083884-0.76880.222083
340.0115570.10590.45795
35-0.068743-0.630.265188
36-0.011181-0.10250.459311

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.386222 & 3.5398 & 0.000328 \tabularnewline
2 & 0.309569 & 2.8372 & 0.002851 \tabularnewline
3 & 0.378069 & 3.4651 & 0.000419 \tabularnewline
4 & -0.189563 & -1.7374 & 0.042993 \tabularnewline
5 & 0.0339 & 0.3107 & 0.3784 \tabularnewline
6 & 0.022444 & 0.2057 & 0.418762 \tabularnewline
7 & -0.136349 & -1.2497 & 0.107448 \tabularnewline
8 & -0.045883 & -0.4205 & 0.337588 \tabularnewline
9 & 0.127081 & 1.1647 & 0.123716 \tabularnewline
10 & -0.077012 & -0.7058 & 0.241125 \tabularnewline
11 & -0.020138 & -0.1846 & 0.427005 \tabularnewline
12 & 0.068451 & 0.6274 & 0.26606 \tabularnewline
13 & -0.020759 & -0.1903 & 0.424783 \tabularnewline
14 & 0.058436 & 0.5356 & 0.296835 \tabularnewline
15 & 0.041872 & 0.3838 & 0.351062 \tabularnewline
16 & -0.032638 & -0.2991 & 0.382788 \tabularnewline
17 & 0.002899 & 0.0266 & 0.489434 \tabularnewline
18 & 0.131832 & 1.2083 & 0.115169 \tabularnewline
19 & -0.117589 & -1.0777 & 0.142122 \tabularnewline
20 & 0.046986 & 0.4306 & 0.333919 \tabularnewline
21 & 0.082822 & 0.7591 & 0.224965 \tabularnewline
22 & -0.238028 & -2.1816 & 0.015968 \tabularnewline
23 & 0.11686 & 1.071 & 0.14361 \tabularnewline
24 & -0.220718 & -2.0229 & 0.023131 \tabularnewline
25 & 0.082089 & 0.7524 & 0.226968 \tabularnewline
26 & -0.023048 & -0.2112 & 0.416607 \tabularnewline
27 & 0.058266 & 0.534 & 0.29737 \tabularnewline
28 & 0.005009 & 0.0459 & 0.481747 \tabularnewline
29 & -0.078627 & -0.7206 & 0.23657 \tabularnewline
30 & -0.034698 & -0.318 & 0.375631 \tabularnewline
31 & 0.002683 & 0.0246 & 0.49022 \tabularnewline
32 & -0.086215 & -0.7902 & 0.215827 \tabularnewline
33 & -0.083884 & -0.7688 & 0.222083 \tabularnewline
34 & 0.011557 & 0.1059 & 0.45795 \tabularnewline
35 & -0.068743 & -0.63 & 0.265188 \tabularnewline
36 & -0.011181 & -0.1025 & 0.459311 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63067&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]0.386222[/C][C]3.5398[/C][C]0.000328[/C][/ROW]
[ROW][C]2[/C][C]0.309569[/C][C]2.8372[/C][C]0.002851[/C][/ROW]
[ROW][C]3[/C][C]0.378069[/C][C]3.4651[/C][C]0.000419[/C][/ROW]
[ROW][C]4[/C][C]-0.189563[/C][C]-1.7374[/C][C]0.042993[/C][/ROW]
[ROW][C]5[/C][C]0.0339[/C][C]0.3107[/C][C]0.3784[/C][/ROW]
[ROW][C]6[/C][C]0.022444[/C][C]0.2057[/C][C]0.418762[/C][/ROW]
[ROW][C]7[/C][C]-0.136349[/C][C]-1.2497[/C][C]0.107448[/C][/ROW]
[ROW][C]8[/C][C]-0.045883[/C][C]-0.4205[/C][C]0.337588[/C][/ROW]
[ROW][C]9[/C][C]0.127081[/C][C]1.1647[/C][C]0.123716[/C][/ROW]
[ROW][C]10[/C][C]-0.077012[/C][C]-0.7058[/C][C]0.241125[/C][/ROW]
[ROW][C]11[/C][C]-0.020138[/C][C]-0.1846[/C][C]0.427005[/C][/ROW]
[ROW][C]12[/C][C]0.068451[/C][C]0.6274[/C][C]0.26606[/C][/ROW]
[ROW][C]13[/C][C]-0.020759[/C][C]-0.1903[/C][C]0.424783[/C][/ROW]
[ROW][C]14[/C][C]0.058436[/C][C]0.5356[/C][C]0.296835[/C][/ROW]
[ROW][C]15[/C][C]0.041872[/C][C]0.3838[/C][C]0.351062[/C][/ROW]
[ROW][C]16[/C][C]-0.032638[/C][C]-0.2991[/C][C]0.382788[/C][/ROW]
[ROW][C]17[/C][C]0.002899[/C][C]0.0266[/C][C]0.489434[/C][/ROW]
[ROW][C]18[/C][C]0.131832[/C][C]1.2083[/C][C]0.115169[/C][/ROW]
[ROW][C]19[/C][C]-0.117589[/C][C]-1.0777[/C][C]0.142122[/C][/ROW]
[ROW][C]20[/C][C]0.046986[/C][C]0.4306[/C][C]0.333919[/C][/ROW]
[ROW][C]21[/C][C]0.082822[/C][C]0.7591[/C][C]0.224965[/C][/ROW]
[ROW][C]22[/C][C]-0.238028[/C][C]-2.1816[/C][C]0.015968[/C][/ROW]
[ROW][C]23[/C][C]0.11686[/C][C]1.071[/C][C]0.14361[/C][/ROW]
[ROW][C]24[/C][C]-0.220718[/C][C]-2.0229[/C][C]0.023131[/C][/ROW]
[ROW][C]25[/C][C]0.082089[/C][C]0.7524[/C][C]0.226968[/C][/ROW]
[ROW][C]26[/C][C]-0.023048[/C][C]-0.2112[/C][C]0.416607[/C][/ROW]
[ROW][C]27[/C][C]0.058266[/C][C]0.534[/C][C]0.29737[/C][/ROW]
[ROW][C]28[/C][C]0.005009[/C][C]0.0459[/C][C]0.481747[/C][/ROW]
[ROW][C]29[/C][C]-0.078627[/C][C]-0.7206[/C][C]0.23657[/C][/ROW]
[ROW][C]30[/C][C]-0.034698[/C][C]-0.318[/C][C]0.375631[/C][/ROW]
[ROW][C]31[/C][C]0.002683[/C][C]0.0246[/C][C]0.49022[/C][/ROW]
[ROW][C]32[/C][C]-0.086215[/C][C]-0.7902[/C][C]0.215827[/C][/ROW]
[ROW][C]33[/C][C]-0.083884[/C][C]-0.7688[/C][C]0.222083[/C][/ROW]
[ROW][C]34[/C][C]0.011557[/C][C]0.1059[/C][C]0.45795[/C][/ROW]
[ROW][C]35[/C][C]-0.068743[/C][C]-0.63[/C][C]0.265188[/C][/ROW]
[ROW][C]36[/C][C]-0.011181[/C][C]-0.1025[/C][C]0.459311[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63067&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63067&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
10.3862223.53980.000328
20.3095692.83720.002851
30.3780693.46510.000419
4-0.189563-1.73740.042993
50.03390.31070.3784
60.0224440.20570.418762
7-0.136349-1.24970.107448
8-0.045883-0.42050.337588
90.1270811.16470.123716
10-0.077012-0.70580.241125
11-0.020138-0.18460.427005
120.0684510.62740.26606
13-0.020759-0.19030.424783
140.0584360.53560.296835
150.0418720.38380.351062
16-0.032638-0.29910.382788
170.0028990.02660.489434
180.1318321.20830.115169
19-0.117589-1.07770.142122
200.0469860.43060.333919
210.0828220.75910.224965
22-0.238028-2.18160.015968
230.116861.0710.14361
24-0.220718-2.02290.023131
250.0820890.75240.226968
26-0.023048-0.21120.416607
270.0582660.5340.29737
280.0050090.04590.481747
29-0.078627-0.72060.23657
30-0.034698-0.3180.375631
310.0026830.02460.49022
32-0.086215-0.79020.215827
33-0.083884-0.76880.222083
340.0115570.10590.45795
35-0.068743-0.630.265188
36-0.011181-0.10250.459311



Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; 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')