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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 08:24:13 -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/t12598541255dmlim6o7895vlv.htm/, Retrieved Fri, 29 Mar 2024 06:02:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62840, Retrieved Fri, 29 Mar 2024 06:02:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
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] [ws8] [2009-11-24 20:12:27] [8b1aef4e7013bd33fbc2a5833375c5f5]
-    D          [(Partial) Autocorrelation Function] [WS8(1)] [2009-11-27 10:20:58] [7d268329e554b8694908ba13e6e6f258]
-   PD            [(Partial) Autocorrelation Function] [WS8(2)] [2009-11-27 10:31:59] [7d268329e554b8694908ba13e6e6f258]
F   P               [(Partial) Autocorrelation Function] [WS8(3)] [2009-11-27 10:38:53] [7d268329e554b8694908ba13e6e6f258]
-   P                 [(Partial) Autocorrelation Function] [WS8(5)] [2009-11-27 11:03:35] [7d268329e554b8694908ba13e6e6f258]
-    D                    [(Partial) Autocorrelation Function] [link] [2009-12-03 15:24:13] [21abcd6b6f55e53f03dbc7aec5059429] [Current]
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Dataseries X:
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9




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=62840&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=62840&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62840&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
10.2775231.92270.030229
2-0.183486-1.27120.104886
3-0.373853-2.59010.006333
4-0.399083-2.76490.004027
5-0.018349-0.12710.449687
60.1490831.03290.153419
70.1467891.0170.15713
80.1307340.90580.184796
9-0.174312-1.20770.116546
10-0.048165-0.33370.370031
110.1009170.69920.243908
12-0.018349-0.12710.449687
130.0435780.30190.38201
14-0.002294-0.01590.493694
15-0.071101-0.49260.31227
160.0298170.20660.418608
17-0.055046-0.38140.352306
180.0298170.20660.418608
19-0.066514-0.46080.323504
200.032110.22250.412448
210.1422020.98520.164732
22-0.020642-0.1430.443439
23-0.068807-0.47670.317865
24-0.103211-0.71510.239016
25-0.036697-0.25420.400196
260.153671.06470.146179
270.0779820.54030.295754
28-0.03211-0.22250.412448
29-0.12844-0.88990.188989
30-0.176606-1.22360.113546
310.0825690.57210.284978
320.2247711.55730.06299
330.1743121.20770.116546
340.0940370.65150.258914
35-0.215596-1.49370.0709
36-0.295872-2.04990.022931

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.277523 & 1.9227 & 0.030229 \tabularnewline
2 & -0.183486 & -1.2712 & 0.104886 \tabularnewline
3 & -0.373853 & -2.5901 & 0.006333 \tabularnewline
4 & -0.399083 & -2.7649 & 0.004027 \tabularnewline
5 & -0.018349 & -0.1271 & 0.449687 \tabularnewline
6 & 0.149083 & 1.0329 & 0.153419 \tabularnewline
7 & 0.146789 & 1.017 & 0.15713 \tabularnewline
8 & 0.130734 & 0.9058 & 0.184796 \tabularnewline
9 & -0.174312 & -1.2077 & 0.116546 \tabularnewline
10 & -0.048165 & -0.3337 & 0.370031 \tabularnewline
11 & 0.100917 & 0.6992 & 0.243908 \tabularnewline
12 & -0.018349 & -0.1271 & 0.449687 \tabularnewline
13 & 0.043578 & 0.3019 & 0.38201 \tabularnewline
14 & -0.002294 & -0.0159 & 0.493694 \tabularnewline
15 & -0.071101 & -0.4926 & 0.31227 \tabularnewline
16 & 0.029817 & 0.2066 & 0.418608 \tabularnewline
17 & -0.055046 & -0.3814 & 0.352306 \tabularnewline
18 & 0.029817 & 0.2066 & 0.418608 \tabularnewline
19 & -0.066514 & -0.4608 & 0.323504 \tabularnewline
20 & 0.03211 & 0.2225 & 0.412448 \tabularnewline
21 & 0.142202 & 0.9852 & 0.164732 \tabularnewline
22 & -0.020642 & -0.143 & 0.443439 \tabularnewline
23 & -0.068807 & -0.4767 & 0.317865 \tabularnewline
24 & -0.103211 & -0.7151 & 0.239016 \tabularnewline
25 & -0.036697 & -0.2542 & 0.400196 \tabularnewline
26 & 0.15367 & 1.0647 & 0.146179 \tabularnewline
27 & 0.077982 & 0.5403 & 0.295754 \tabularnewline
28 & -0.03211 & -0.2225 & 0.412448 \tabularnewline
29 & -0.12844 & -0.8899 & 0.188989 \tabularnewline
30 & -0.176606 & -1.2236 & 0.113546 \tabularnewline
31 & 0.082569 & 0.5721 & 0.284978 \tabularnewline
32 & 0.224771 & 1.5573 & 0.06299 \tabularnewline
33 & 0.174312 & 1.2077 & 0.116546 \tabularnewline
34 & 0.094037 & 0.6515 & 0.258914 \tabularnewline
35 & -0.215596 & -1.4937 & 0.0709 \tabularnewline
36 & -0.295872 & -2.0499 & 0.022931 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62840&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]0.277523[/C][C]1.9227[/C][C]0.030229[/C][/ROW]
[ROW][C]2[/C][C]-0.183486[/C][C]-1.2712[/C][C]0.104886[/C][/ROW]
[ROW][C]3[/C][C]-0.373853[/C][C]-2.5901[/C][C]0.006333[/C][/ROW]
[ROW][C]4[/C][C]-0.399083[/C][C]-2.7649[/C][C]0.004027[/C][/ROW]
[ROW][C]5[/C][C]-0.018349[/C][C]-0.1271[/C][C]0.449687[/C][/ROW]
[ROW][C]6[/C][C]0.149083[/C][C]1.0329[/C][C]0.153419[/C][/ROW]
[ROW][C]7[/C][C]0.146789[/C][C]1.017[/C][C]0.15713[/C][/ROW]
[ROW][C]8[/C][C]0.130734[/C][C]0.9058[/C][C]0.184796[/C][/ROW]
[ROW][C]9[/C][C]-0.174312[/C][C]-1.2077[/C][C]0.116546[/C][/ROW]
[ROW][C]10[/C][C]-0.048165[/C][C]-0.3337[/C][C]0.370031[/C][/ROW]
[ROW][C]11[/C][C]0.100917[/C][C]0.6992[/C][C]0.243908[/C][/ROW]
[ROW][C]12[/C][C]-0.018349[/C][C]-0.1271[/C][C]0.449687[/C][/ROW]
[ROW][C]13[/C][C]0.043578[/C][C]0.3019[/C][C]0.38201[/C][/ROW]
[ROW][C]14[/C][C]-0.002294[/C][C]-0.0159[/C][C]0.493694[/C][/ROW]
[ROW][C]15[/C][C]-0.071101[/C][C]-0.4926[/C][C]0.31227[/C][/ROW]
[ROW][C]16[/C][C]0.029817[/C][C]0.2066[/C][C]0.418608[/C][/ROW]
[ROW][C]17[/C][C]-0.055046[/C][C]-0.3814[/C][C]0.352306[/C][/ROW]
[ROW][C]18[/C][C]0.029817[/C][C]0.2066[/C][C]0.418608[/C][/ROW]
[ROW][C]19[/C][C]-0.066514[/C][C]-0.4608[/C][C]0.323504[/C][/ROW]
[ROW][C]20[/C][C]0.03211[/C][C]0.2225[/C][C]0.412448[/C][/ROW]
[ROW][C]21[/C][C]0.142202[/C][C]0.9852[/C][C]0.164732[/C][/ROW]
[ROW][C]22[/C][C]-0.020642[/C][C]-0.143[/C][C]0.443439[/C][/ROW]
[ROW][C]23[/C][C]-0.068807[/C][C]-0.4767[/C][C]0.317865[/C][/ROW]
[ROW][C]24[/C][C]-0.103211[/C][C]-0.7151[/C][C]0.239016[/C][/ROW]
[ROW][C]25[/C][C]-0.036697[/C][C]-0.2542[/C][C]0.400196[/C][/ROW]
[ROW][C]26[/C][C]0.15367[/C][C]1.0647[/C][C]0.146179[/C][/ROW]
[ROW][C]27[/C][C]0.077982[/C][C]0.5403[/C][C]0.295754[/C][/ROW]
[ROW][C]28[/C][C]-0.03211[/C][C]-0.2225[/C][C]0.412448[/C][/ROW]
[ROW][C]29[/C][C]-0.12844[/C][C]-0.8899[/C][C]0.188989[/C][/ROW]
[ROW][C]30[/C][C]-0.176606[/C][C]-1.2236[/C][C]0.113546[/C][/ROW]
[ROW][C]31[/C][C]0.082569[/C][C]0.5721[/C][C]0.284978[/C][/ROW]
[ROW][C]32[/C][C]0.224771[/C][C]1.5573[/C][C]0.06299[/C][/ROW]
[ROW][C]33[/C][C]0.174312[/C][C]1.2077[/C][C]0.116546[/C][/ROW]
[ROW][C]34[/C][C]0.094037[/C][C]0.6515[/C][C]0.258914[/C][/ROW]
[ROW][C]35[/C][C]-0.215596[/C][C]-1.4937[/C][C]0.0709[/C][/ROW]
[ROW][C]36[/C][C]-0.295872[/C][C]-2.0499[/C][C]0.022931[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62840&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62840&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
10.2775231.92270.030229
2-0.183486-1.27120.104886
3-0.373853-2.59010.006333
4-0.399083-2.76490.004027
5-0.018349-0.12710.449687
60.1490831.03290.153419
70.1467891.0170.15713
80.1307340.90580.184796
9-0.174312-1.20770.116546
10-0.048165-0.33370.370031
110.1009170.69920.243908
12-0.018349-0.12710.449687
130.0435780.30190.38201
14-0.002294-0.01590.493694
15-0.071101-0.49260.31227
160.0298170.20660.418608
17-0.055046-0.38140.352306
180.0298170.20660.418608
19-0.066514-0.46080.323504
200.032110.22250.412448
210.1422020.98520.164732
22-0.020642-0.1430.443439
23-0.068807-0.47670.317865
24-0.103211-0.71510.239016
25-0.036697-0.25420.400196
260.153671.06470.146179
270.0779820.54030.295754
28-0.03211-0.22250.412448
29-0.12844-0.88990.188989
30-0.176606-1.22360.113546
310.0825690.57210.284978
320.2247711.55730.06299
330.1743121.20770.116546
340.0940370.65150.258914
35-0.215596-1.49370.0709
36-0.295872-2.04990.022931







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2775231.92270.030229
2-0.282243-1.95540.028183
3-0.271033-1.87780.033248
4-0.32211-2.23160.015172
50.0320880.22230.412507
6-0.10898-0.7550.226958
7-0.083182-0.57630.283552
80.011980.0830.467099
9-0.249937-1.73160.044883
100.1217580.84360.201549
110.0750130.51970.302828
12-0.13069-0.90540.184875
130.0238280.16510.434785
140.0592540.41050.341624
15-0.032539-0.22540.411299
160.0381440.26430.396351
17-0.049446-0.34260.366707
180.0186950.12950.448744
19-0.179717-1.24510.109567
200.2306431.59790.058309
21-0.017207-0.11920.452802
22-0.136302-0.94430.174866
230.0392690.27210.39337
24-0.094678-0.6560.257494
250.0755640.52350.30151
260.0891310.61750.269906
27-0.042348-0.29340.385244
28-0.149664-1.03690.152489
29-0.033107-0.22940.409776
300.0306220.21220.416441
310.0038750.02680.489346
320.1019030.7060.241799
330.0986410.68340.248819
340.0188110.13030.448427
350.0158690.10990.456456
36-0.111918-0.77540.220957

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.277523 & 1.9227 & 0.030229 \tabularnewline
2 & -0.282243 & -1.9554 & 0.028183 \tabularnewline
3 & -0.271033 & -1.8778 & 0.033248 \tabularnewline
4 & -0.32211 & -2.2316 & 0.015172 \tabularnewline
5 & 0.032088 & 0.2223 & 0.412507 \tabularnewline
6 & -0.10898 & -0.755 & 0.226958 \tabularnewline
7 & -0.083182 & -0.5763 & 0.283552 \tabularnewline
8 & 0.01198 & 0.083 & 0.467099 \tabularnewline
9 & -0.249937 & -1.7316 & 0.044883 \tabularnewline
10 & 0.121758 & 0.8436 & 0.201549 \tabularnewline
11 & 0.075013 & 0.5197 & 0.302828 \tabularnewline
12 & -0.13069 & -0.9054 & 0.184875 \tabularnewline
13 & 0.023828 & 0.1651 & 0.434785 \tabularnewline
14 & 0.059254 & 0.4105 & 0.341624 \tabularnewline
15 & -0.032539 & -0.2254 & 0.411299 \tabularnewline
16 & 0.038144 & 0.2643 & 0.396351 \tabularnewline
17 & -0.049446 & -0.3426 & 0.366707 \tabularnewline
18 & 0.018695 & 0.1295 & 0.448744 \tabularnewline
19 & -0.179717 & -1.2451 & 0.109567 \tabularnewline
20 & 0.230643 & 1.5979 & 0.058309 \tabularnewline
21 & -0.017207 & -0.1192 & 0.452802 \tabularnewline
22 & -0.136302 & -0.9443 & 0.174866 \tabularnewline
23 & 0.039269 & 0.2721 & 0.39337 \tabularnewline
24 & -0.094678 & -0.656 & 0.257494 \tabularnewline
25 & 0.075564 & 0.5235 & 0.30151 \tabularnewline
26 & 0.089131 & 0.6175 & 0.269906 \tabularnewline
27 & -0.042348 & -0.2934 & 0.385244 \tabularnewline
28 & -0.149664 & -1.0369 & 0.152489 \tabularnewline
29 & -0.033107 & -0.2294 & 0.409776 \tabularnewline
30 & 0.030622 & 0.2122 & 0.416441 \tabularnewline
31 & 0.003875 & 0.0268 & 0.489346 \tabularnewline
32 & 0.101903 & 0.706 & 0.241799 \tabularnewline
33 & 0.098641 & 0.6834 & 0.248819 \tabularnewline
34 & 0.018811 & 0.1303 & 0.448427 \tabularnewline
35 & 0.015869 & 0.1099 & 0.456456 \tabularnewline
36 & -0.111918 & -0.7754 & 0.220957 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62840&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]0.277523[/C][C]1.9227[/C][C]0.030229[/C][/ROW]
[ROW][C]2[/C][C]-0.282243[/C][C]-1.9554[/C][C]0.028183[/C][/ROW]
[ROW][C]3[/C][C]-0.271033[/C][C]-1.8778[/C][C]0.033248[/C][/ROW]
[ROW][C]4[/C][C]-0.32211[/C][C]-2.2316[/C][C]0.015172[/C][/ROW]
[ROW][C]5[/C][C]0.032088[/C][C]0.2223[/C][C]0.412507[/C][/ROW]
[ROW][C]6[/C][C]-0.10898[/C][C]-0.755[/C][C]0.226958[/C][/ROW]
[ROW][C]7[/C][C]-0.083182[/C][C]-0.5763[/C][C]0.283552[/C][/ROW]
[ROW][C]8[/C][C]0.01198[/C][C]0.083[/C][C]0.467099[/C][/ROW]
[ROW][C]9[/C][C]-0.249937[/C][C]-1.7316[/C][C]0.044883[/C][/ROW]
[ROW][C]10[/C][C]0.121758[/C][C]0.8436[/C][C]0.201549[/C][/ROW]
[ROW][C]11[/C][C]0.075013[/C][C]0.5197[/C][C]0.302828[/C][/ROW]
[ROW][C]12[/C][C]-0.13069[/C][C]-0.9054[/C][C]0.184875[/C][/ROW]
[ROW][C]13[/C][C]0.023828[/C][C]0.1651[/C][C]0.434785[/C][/ROW]
[ROW][C]14[/C][C]0.059254[/C][C]0.4105[/C][C]0.341624[/C][/ROW]
[ROW][C]15[/C][C]-0.032539[/C][C]-0.2254[/C][C]0.411299[/C][/ROW]
[ROW][C]16[/C][C]0.038144[/C][C]0.2643[/C][C]0.396351[/C][/ROW]
[ROW][C]17[/C][C]-0.049446[/C][C]-0.3426[/C][C]0.366707[/C][/ROW]
[ROW][C]18[/C][C]0.018695[/C][C]0.1295[/C][C]0.448744[/C][/ROW]
[ROW][C]19[/C][C]-0.179717[/C][C]-1.2451[/C][C]0.109567[/C][/ROW]
[ROW][C]20[/C][C]0.230643[/C][C]1.5979[/C][C]0.058309[/C][/ROW]
[ROW][C]21[/C][C]-0.017207[/C][C]-0.1192[/C][C]0.452802[/C][/ROW]
[ROW][C]22[/C][C]-0.136302[/C][C]-0.9443[/C][C]0.174866[/C][/ROW]
[ROW][C]23[/C][C]0.039269[/C][C]0.2721[/C][C]0.39337[/C][/ROW]
[ROW][C]24[/C][C]-0.094678[/C][C]-0.656[/C][C]0.257494[/C][/ROW]
[ROW][C]25[/C][C]0.075564[/C][C]0.5235[/C][C]0.30151[/C][/ROW]
[ROW][C]26[/C][C]0.089131[/C][C]0.6175[/C][C]0.269906[/C][/ROW]
[ROW][C]27[/C][C]-0.042348[/C][C]-0.2934[/C][C]0.385244[/C][/ROW]
[ROW][C]28[/C][C]-0.149664[/C][C]-1.0369[/C][C]0.152489[/C][/ROW]
[ROW][C]29[/C][C]-0.033107[/C][C]-0.2294[/C][C]0.409776[/C][/ROW]
[ROW][C]30[/C][C]0.030622[/C][C]0.2122[/C][C]0.416441[/C][/ROW]
[ROW][C]31[/C][C]0.003875[/C][C]0.0268[/C][C]0.489346[/C][/ROW]
[ROW][C]32[/C][C]0.101903[/C][C]0.706[/C][C]0.241799[/C][/ROW]
[ROW][C]33[/C][C]0.098641[/C][C]0.6834[/C][C]0.248819[/C][/ROW]
[ROW][C]34[/C][C]0.018811[/C][C]0.1303[/C][C]0.448427[/C][/ROW]
[ROW][C]35[/C][C]0.015869[/C][C]0.1099[/C][C]0.456456[/C][/ROW]
[ROW][C]36[/C][C]-0.111918[/C][C]-0.7754[/C][C]0.220957[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62840&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62840&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
10.2775231.92270.030229
2-0.282243-1.95540.028183
3-0.271033-1.87780.033248
4-0.32211-2.23160.015172
50.0320880.22230.412507
6-0.10898-0.7550.226958
7-0.083182-0.57630.283552
80.011980.0830.467099
9-0.249937-1.73160.044883
100.1217580.84360.201549
110.0750130.51970.302828
12-0.13069-0.90540.184875
130.0238280.16510.434785
140.0592540.41050.341624
15-0.032539-0.22540.411299
160.0381440.26430.396351
17-0.049446-0.34260.366707
180.0186950.12950.448744
19-0.179717-1.24510.109567
200.2306431.59790.058309
21-0.017207-0.11920.452802
22-0.136302-0.94430.174866
230.0392690.27210.39337
24-0.094678-0.6560.257494
250.0755640.52350.30151
260.0891310.61750.269906
27-0.042348-0.29340.385244
28-0.149664-1.03690.152489
29-0.033107-0.22940.409776
300.0306220.21220.416441
310.0038750.02680.489346
320.1019030.7060.241799
330.0986410.68340.248819
340.0188110.13030.448427
350.0158690.10990.456456
36-0.111918-0.77540.220957



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')