## Free Statistics

of Irreproducible Research!

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 computationTue, 24 Nov 2009 09:09:21 -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/24/t1259079079sqtezyb0ktfta11.htm/, Retrieved Thu, 12 Sep 2024 15:41:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59143, Retrieved Thu, 12 Sep 2024 15:41:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws8ma1.1
Estimated Impact190
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 16:09:21] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
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Dataseries X:
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59143&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]0 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=59143&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59143&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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 0 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.962625 7.4565 0 2 0.910043 7.0492 0 3 0.850015 6.5842 0 4 0.779442 6.0375 0 5 0.699878 5.4212 1e-06 6 0.605173 4.6877 8e-06 7 0.507643 3.9322 0.00011 8 0.413559 3.2034 0.001088 9 0.314939 2.4395 0.00884 10 0.21472 1.6632 0.050742 11 0.125841 0.9748 0.166796 12 0.035056 0.2715 0.393453 13 -0.039972 -0.3096 0.378961 14 -0.110431 -0.8554 0.197867 15 -0.182427 -1.4131 0.0814 16 -0.240482 -1.8628 0.033696 17 -0.292184 -2.2632 0.013626 18 -0.33504 -2.5952 0.005933 19 -0.373305 -2.8916 0.002666 20 -0.412711 -3.1968 0.001109 21 -0.449163 -3.4792 0.000471 22 -0.470848 -3.6472 0.000278 23 -0.482541 -3.7377 0.000208 24 -0.479158 -3.7115 0.000226 25 -0.470728 -3.6462 0.000279 26 -0.46077 -3.5691 0.000356 27 -0.437284 -3.3872 0.000626 28 -0.408631 -3.1652 0.001217 29 -0.380043 -2.9438 0.002303 30 -0.354663 -2.7472 0.003962 31 -0.32903 -2.5487 0.006695 32 -0.295284 -2.2873 0.012861 33 -0.262003 -2.0295 0.023426 34 -0.230235 -1.7834 0.03979 35 -0.20207 -1.5652 0.061395 36 -0.168457 -1.3049 0.098461

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.962625 & 7.4565 & 0 \tabularnewline
2 & 0.910043 & 7.0492 & 0 \tabularnewline
3 & 0.850015 & 6.5842 & 0 \tabularnewline
4 & 0.779442 & 6.0375 & 0 \tabularnewline
5 & 0.699878 & 5.4212 & 1e-06 \tabularnewline
6 & 0.605173 & 4.6877 & 8e-06 \tabularnewline
7 & 0.507643 & 3.9322 & 0.00011 \tabularnewline
8 & 0.413559 & 3.2034 & 0.001088 \tabularnewline
9 & 0.314939 & 2.4395 & 0.00884 \tabularnewline
10 & 0.21472 & 1.6632 & 0.050742 \tabularnewline
11 & 0.125841 & 0.9748 & 0.166796 \tabularnewline
12 & 0.035056 & 0.2715 & 0.393453 \tabularnewline
13 & -0.039972 & -0.3096 & 0.378961 \tabularnewline
14 & -0.110431 & -0.8554 & 0.197867 \tabularnewline
15 & -0.182427 & -1.4131 & 0.0814 \tabularnewline
16 & -0.240482 & -1.8628 & 0.033696 \tabularnewline
17 & -0.292184 & -2.2632 & 0.013626 \tabularnewline
18 & -0.33504 & -2.5952 & 0.005933 \tabularnewline
19 & -0.373305 & -2.8916 & 0.002666 \tabularnewline
20 & -0.412711 & -3.1968 & 0.001109 \tabularnewline
21 & -0.449163 & -3.4792 & 0.000471 \tabularnewline
22 & -0.470848 & -3.6472 & 0.000278 \tabularnewline
23 & -0.482541 & -3.7377 & 0.000208 \tabularnewline
24 & -0.479158 & -3.7115 & 0.000226 \tabularnewline
25 & -0.470728 & -3.6462 & 0.000279 \tabularnewline
26 & -0.46077 & -3.5691 & 0.000356 \tabularnewline
27 & -0.437284 & -3.3872 & 0.000626 \tabularnewline
28 & -0.408631 & -3.1652 & 0.001217 \tabularnewline
29 & -0.380043 & -2.9438 & 0.002303 \tabularnewline
30 & -0.354663 & -2.7472 & 0.003962 \tabularnewline
31 & -0.32903 & -2.5487 & 0.006695 \tabularnewline
32 & -0.295284 & -2.2873 & 0.012861 \tabularnewline
33 & -0.262003 & -2.0295 & 0.023426 \tabularnewline
34 & -0.230235 & -1.7834 & 0.03979 \tabularnewline
35 & -0.20207 & -1.5652 & 0.061395 \tabularnewline
36 & -0.168457 & -1.3049 & 0.098461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59143&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]0.962625[/C][C]7.4565[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.910043[/C][C]7.0492[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.850015[/C][C]6.5842[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.779442[/C][C]6.0375[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.699878[/C][C]5.4212[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.605173[/C][C]4.6877[/C][C]8e-06[/C][/ROW]
[ROW][C]7[/C][C]0.507643[/C][C]3.9322[/C][C]0.00011[/C][/ROW]
[ROW][C]8[/C][C]0.413559[/C][C]3.2034[/C][C]0.001088[/C][/ROW]
[ROW][C]9[/C][C]0.314939[/C][C]2.4395[/C][C]0.00884[/C][/ROW]
[ROW][C]10[/C][C]0.21472[/C][C]1.6632[/C][C]0.050742[/C][/ROW]
[ROW][C]11[/C][C]0.125841[/C][C]0.9748[/C][C]0.166796[/C][/ROW]
[ROW][C]12[/C][C]0.035056[/C][C]0.2715[/C][C]0.393453[/C][/ROW]
[ROW][C]13[/C][C]-0.039972[/C][C]-0.3096[/C][C]0.378961[/C][/ROW]
[ROW][C]14[/C][C]-0.110431[/C][C]-0.8554[/C][C]0.197867[/C][/ROW]
[ROW][C]15[/C][C]-0.182427[/C][C]-1.4131[/C][C]0.0814[/C][/ROW]
[ROW][C]16[/C][C]-0.240482[/C][C]-1.8628[/C][C]0.033696[/C][/ROW]
[ROW][C]17[/C][C]-0.292184[/C][C]-2.2632[/C][C]0.013626[/C][/ROW]
[ROW][C]18[/C][C]-0.33504[/C][C]-2.5952[/C][C]0.005933[/C][/ROW]
[ROW][C]19[/C][C]-0.373305[/C][C]-2.8916[/C][C]0.002666[/C][/ROW]
[ROW][C]20[/C][C]-0.412711[/C][C]-3.1968[/C][C]0.001109[/C][/ROW]
[ROW][C]21[/C][C]-0.449163[/C][C]-3.4792[/C][C]0.000471[/C][/ROW]
[ROW][C]22[/C][C]-0.470848[/C][C]-3.6472[/C][C]0.000278[/C][/ROW]
[ROW][C]23[/C][C]-0.482541[/C][C]-3.7377[/C][C]0.000208[/C][/ROW]
[ROW][C]24[/C][C]-0.479158[/C][C]-3.7115[/C][C]0.000226[/C][/ROW]
[ROW][C]25[/C][C]-0.470728[/C][C]-3.6462[/C][C]0.000279[/C][/ROW]
[ROW][C]26[/C][C]-0.46077[/C][C]-3.5691[/C][C]0.000356[/C][/ROW]
[ROW][C]27[/C][C]-0.437284[/C][C]-3.3872[/C][C]0.000626[/C][/ROW]
[ROW][C]28[/C][C]-0.408631[/C][C]-3.1652[/C][C]0.001217[/C][/ROW]
[ROW][C]29[/C][C]-0.380043[/C][C]-2.9438[/C][C]0.002303[/C][/ROW]
[ROW][C]30[/C][C]-0.354663[/C][C]-2.7472[/C][C]0.003962[/C][/ROW]
[ROW][C]31[/C][C]-0.32903[/C][C]-2.5487[/C][C]0.006695[/C][/ROW]
[ROW][C]32[/C][C]-0.295284[/C][C]-2.2873[/C][C]0.012861[/C][/ROW]
[ROW][C]33[/C][C]-0.262003[/C][C]-2.0295[/C][C]0.023426[/C][/ROW]
[ROW][C]34[/C][C]-0.230235[/C][C]-1.7834[/C][C]0.03979[/C][/ROW]
[ROW][C]35[/C][C]-0.20207[/C][C]-1.5652[/C][C]0.061395[/C][/ROW]
[ROW][C]36[/C][C]-0.168457[/C][C]-1.3049[/C][C]0.098461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59143&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59143&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 k ACF(k) T-STAT P-value 1 0.962625 7.4565 0 2 0.910043 7.0492 0 3 0.850015 6.5842 0 4 0.779442 6.0375 0 5 0.699878 5.4212 1e-06 6 0.605173 4.6877 8e-06 7 0.507643 3.9322 0.00011 8 0.413559 3.2034 0.001088 9 0.314939 2.4395 0.00884 10 0.21472 1.6632 0.050742 11 0.125841 0.9748 0.166796 12 0.035056 0.2715 0.393453 13 -0.039972 -0.3096 0.378961 14 -0.110431 -0.8554 0.197867 15 -0.182427 -1.4131 0.0814 16 -0.240482 -1.8628 0.033696 17 -0.292184 -2.2632 0.013626 18 -0.33504 -2.5952 0.005933 19 -0.373305 -2.8916 0.002666 20 -0.412711 -3.1968 0.001109 21 -0.449163 -3.4792 0.000471 22 -0.470848 -3.6472 0.000278 23 -0.482541 -3.7377 0.000208 24 -0.479158 -3.7115 0.000226 25 -0.470728 -3.6462 0.000279 26 -0.46077 -3.5691 0.000356 27 -0.437284 -3.3872 0.000626 28 -0.408631 -3.1652 0.001217 29 -0.380043 -2.9438 0.002303 30 -0.354663 -2.7472 0.003962 31 -0.32903 -2.5487 0.006695 32 -0.295284 -2.2873 0.012861 33 -0.262003 -2.0295 0.023426 34 -0.230235 -1.7834 0.03979 35 -0.20207 -1.5652 0.061395 36 -0.168457 -1.3049 0.098461

 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.962625 7.4565 0 2 -0.226367 -1.7534 0.042317 3 -0.092148 -0.7138 0.239066 4 -0.153423 -1.1884 0.119677 5 -0.12001 -0.9296 0.178153 6 -0.226221 -1.7523 0.042416 7 -0.025709 -0.1991 0.421414 8 0.015877 0.123 0.451266 9 -0.116592 -0.9031 0.185038 10 -0.067854 -0.5256 0.300554 11 0.118298 0.9163 0.181581 12 -0.169362 -1.3119 0.09728 13 0.156416 1.2116 0.115209 14 -0.091235 -0.7067 0.241243 15 -0.132564 -1.0268 0.154309 16 0.053615 0.4153 0.339702 17 -0.042464 -0.3289 0.37168 18 -0.026315 -0.2038 0.419585 19 -0.086914 -0.6732 0.251693 20 -0.101692 -0.7877 0.216986 21 -0.10513 -0.8143 0.209338 22 0.076449 0.5922 0.277981 23 0.106781 0.8271 0.205722 24 0.081602 0.6321 0.264867 25 -0.041162 -0.3188 0.375479 26 -0.039796 -0.3083 0.379476 27 0.002349 0.0182 0.49277 28 0.0028 0.0217 0.491383 29 -0.106421 -0.8243 0.206507 30 -0.142029 -1.1002 0.137831 31 -0.047477 -0.3678 0.357176 32 0.064404 0.4989 0.309846 33 -0.064994 -0.5034 0.308248 34 0.104031 0.8058 0.211764 35 -0.089159 -0.6906 0.246233 36 0.088406 0.6848 0.248056

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.962625 & 7.4565 & 0 \tabularnewline
2 & -0.226367 & -1.7534 & 0.042317 \tabularnewline
3 & -0.092148 & -0.7138 & 0.239066 \tabularnewline
4 & -0.153423 & -1.1884 & 0.119677 \tabularnewline
5 & -0.12001 & -0.9296 & 0.178153 \tabularnewline
6 & -0.226221 & -1.7523 & 0.042416 \tabularnewline
7 & -0.025709 & -0.1991 & 0.421414 \tabularnewline
8 & 0.015877 & 0.123 & 0.451266 \tabularnewline
9 & -0.116592 & -0.9031 & 0.185038 \tabularnewline
10 & -0.067854 & -0.5256 & 0.300554 \tabularnewline
11 & 0.118298 & 0.9163 & 0.181581 \tabularnewline
12 & -0.169362 & -1.3119 & 0.09728 \tabularnewline
13 & 0.156416 & 1.2116 & 0.115209 \tabularnewline
14 & -0.091235 & -0.7067 & 0.241243 \tabularnewline
15 & -0.132564 & -1.0268 & 0.154309 \tabularnewline
16 & 0.053615 & 0.4153 & 0.339702 \tabularnewline
17 & -0.042464 & -0.3289 & 0.37168 \tabularnewline
18 & -0.026315 & -0.2038 & 0.419585 \tabularnewline
19 & -0.086914 & -0.6732 & 0.251693 \tabularnewline
20 & -0.101692 & -0.7877 & 0.216986 \tabularnewline
21 & -0.10513 & -0.8143 & 0.209338 \tabularnewline
22 & 0.076449 & 0.5922 & 0.277981 \tabularnewline
23 & 0.106781 & 0.8271 & 0.205722 \tabularnewline
24 & 0.081602 & 0.6321 & 0.264867 \tabularnewline
25 & -0.041162 & -0.3188 & 0.375479 \tabularnewline
26 & -0.039796 & -0.3083 & 0.379476 \tabularnewline
27 & 0.002349 & 0.0182 & 0.49277 \tabularnewline
28 & 0.0028 & 0.0217 & 0.491383 \tabularnewline
29 & -0.106421 & -0.8243 & 0.206507 \tabularnewline
30 & -0.142029 & -1.1002 & 0.137831 \tabularnewline
31 & -0.047477 & -0.3678 & 0.357176 \tabularnewline
32 & 0.064404 & 0.4989 & 0.309846 \tabularnewline
33 & -0.064994 & -0.5034 & 0.308248 \tabularnewline
34 & 0.104031 & 0.8058 & 0.211764 \tabularnewline
35 & -0.089159 & -0.6906 & 0.246233 \tabularnewline
36 & 0.088406 & 0.6848 & 0.248056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59143&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]0.962625[/C][C]7.4565[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.226367[/C][C]-1.7534[/C][C]0.042317[/C][/ROW]
[ROW][C]3[/C][C]-0.092148[/C][C]-0.7138[/C][C]0.239066[/C][/ROW]
[ROW][C]4[/C][C]-0.153423[/C][C]-1.1884[/C][C]0.119677[/C][/ROW]
[ROW][C]5[/C][C]-0.12001[/C][C]-0.9296[/C][C]0.178153[/C][/ROW]
[ROW][C]6[/C][C]-0.226221[/C][C]-1.7523[/C][C]0.042416[/C][/ROW]
[ROW][C]7[/C][C]-0.025709[/C][C]-0.1991[/C][C]0.421414[/C][/ROW]
[ROW][C]8[/C][C]0.015877[/C][C]0.123[/C][C]0.451266[/C][/ROW]
[ROW][C]9[/C][C]-0.116592[/C][C]-0.9031[/C][C]0.185038[/C][/ROW]
[ROW][C]10[/C][C]-0.067854[/C][C]-0.5256[/C][C]0.300554[/C][/ROW]
[ROW][C]11[/C][C]0.118298[/C][C]0.9163[/C][C]0.181581[/C][/ROW]
[ROW][C]12[/C][C]-0.169362[/C][C]-1.3119[/C][C]0.09728[/C][/ROW]
[ROW][C]13[/C][C]0.156416[/C][C]1.2116[/C][C]0.115209[/C][/ROW]
[ROW][C]14[/C][C]-0.091235[/C][C]-0.7067[/C][C]0.241243[/C][/ROW]
[ROW][C]15[/C][C]-0.132564[/C][C]-1.0268[/C][C]0.154309[/C][/ROW]
[ROW][C]16[/C][C]0.053615[/C][C]0.4153[/C][C]0.339702[/C][/ROW]
[ROW][C]17[/C][C]-0.042464[/C][C]-0.3289[/C][C]0.37168[/C][/ROW]
[ROW][C]18[/C][C]-0.026315[/C][C]-0.2038[/C][C]0.419585[/C][/ROW]
[ROW][C]19[/C][C]-0.086914[/C][C]-0.6732[/C][C]0.251693[/C][/ROW]
[ROW][C]20[/C][C]-0.101692[/C][C]-0.7877[/C][C]0.216986[/C][/ROW]
[ROW][C]21[/C][C]-0.10513[/C][C]-0.8143[/C][C]0.209338[/C][/ROW]
[ROW][C]22[/C][C]0.076449[/C][C]0.5922[/C][C]0.277981[/C][/ROW]
[ROW][C]23[/C][C]0.106781[/C][C]0.8271[/C][C]0.205722[/C][/ROW]
[ROW][C]24[/C][C]0.081602[/C][C]0.6321[/C][C]0.264867[/C][/ROW]
[ROW][C]25[/C][C]-0.041162[/C][C]-0.3188[/C][C]0.375479[/C][/ROW]
[ROW][C]26[/C][C]-0.039796[/C][C]-0.3083[/C][C]0.379476[/C][/ROW]
[ROW][C]27[/C][C]0.002349[/C][C]0.0182[/C][C]0.49277[/C][/ROW]
[ROW][C]28[/C][C]0.0028[/C][C]0.0217[/C][C]0.491383[/C][/ROW]
[ROW][C]29[/C][C]-0.106421[/C][C]-0.8243[/C][C]0.206507[/C][/ROW]
[ROW][C]30[/C][C]-0.142029[/C][C]-1.1002[/C][C]0.137831[/C][/ROW]
[ROW][C]31[/C][C]-0.047477[/C][C]-0.3678[/C][C]0.357176[/C][/ROW]
[ROW][C]32[/C][C]0.064404[/C][C]0.4989[/C][C]0.309846[/C][/ROW]
[ROW][C]33[/C][C]-0.064994[/C][C]-0.5034[/C][C]0.308248[/C][/ROW]
[ROW][C]34[/C][C]0.104031[/C][C]0.8058[/C][C]0.211764[/C][/ROW]
[ROW][C]35[/C][C]-0.089159[/C][C]-0.6906[/C][C]0.246233[/C][/ROW]
[ROW][C]36[/C][C]0.088406[/C][C]0.6848[/C][C]0.248056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59143&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59143&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 k PACF(k) T-STAT P-value 1 0.962625 7.4565 0 2 -0.226367 -1.7534 0.042317 3 -0.092148 -0.7138 0.239066 4 -0.153423 -1.1884 0.119677 5 -0.12001 -0.9296 0.178153 6 -0.226221 -1.7523 0.042416 7 -0.025709 -0.1991 0.421414 8 0.015877 0.123 0.451266 9 -0.116592 -0.9031 0.185038 10 -0.067854 -0.5256 0.300554 11 0.118298 0.9163 0.181581 12 -0.169362 -1.3119 0.09728 13 0.156416 1.2116 0.115209 14 -0.091235 -0.7067 0.241243 15 -0.132564 -1.0268 0.154309 16 0.053615 0.4153 0.339702 17 -0.042464 -0.3289 0.37168 18 -0.026315 -0.2038 0.419585 19 -0.086914 -0.6732 0.251693 20 -0.101692 -0.7877 0.216986 21 -0.10513 -0.8143 0.209338 22 0.076449 0.5922 0.277981 23 0.106781 0.8271 0.205722 24 0.081602 0.6321 0.264867 25 -0.041162 -0.3188 0.375479 26 -0.039796 -0.3083 0.379476 27 0.002349 0.0182 0.49277 28 0.0028 0.0217 0.491383 29 -0.106421 -0.8243 0.206507 30 -0.142029 -1.1002 0.137831 31 -0.047477 -0.3678 0.357176 32 0.064404 0.4989 0.309846 33 -0.064994 -0.5034 0.308248 34 0.104031 0.8058 0.211764 35 -0.089159 -0.6906 0.246233 36 0.088406 0.6848 0.248056

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)
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.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
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)