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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 computationFri, 27 Nov 2009 08:59:35 -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/t125933763342mzvd37jyeiold.htm/, Retrieved Mon, 29 Apr 2024 18:03:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60929, Retrieved Mon, 29 Apr 2024 18:03:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117
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 12:26:39] [b98453cac15ba1066b407e146608df68]
- R  D          [(Partial) Autocorrelation Function] [] [2009-11-27 15:59:35] [1c773da0103d9327c2f1f790e2d74438] [Current]
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Dataseries X:
1.4816
1.4562
1.4268
1.4088
1.4016
1.3650
1.3190
1.3050
1.2785
1.3239
1.3449
1.2732
1.3322
1.4369
1.4975
1.5770
1.5553
1.5557
1.5750
1.5527
1.4748
1.4718
1.4570
1.4684
1.4227
1.3896
1.3622
1.3716
1.3419
1.3511
1.3516
1.3242
1.3074
1.2999
1.3213
1.2881




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=60929&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=60929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60929&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
10.4240742.03380.026833
20.2015950.96680.171846
30.0757970.36350.359772
40.1476450.70810.243004
50.1933280.92720.181734
6-0.070283-0.33710.369562
7-0.347637-1.66720.054517
8-0.157265-0.75420.229186
9-0.081222-0.38950.350235
10-0.127075-0.60940.274107
11-0.271489-1.3020.102901
12-0.39739-1.90580.034624
13-0.192126-0.92140.183202
14-0.04065-0.1950.423571
150.0237440.11390.455164
160.0118340.05680.477617
170.0205550.09860.461163
180.0264610.12690.450061
190.1175770.56390.289147
20-0.012155-0.05830.477009
210.009480.04550.482064
22-0.054799-0.26280.39752
23NANANA
24NANANA
25NANANA
26NANANA
27NANANA
28NANANA
29NANANA
30NANANA
31NANANA
32NANANA
33NANANA
34NANANA
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.424074 & 2.0338 & 0.026833 \tabularnewline
2 & 0.201595 & 0.9668 & 0.171846 \tabularnewline
3 & 0.075797 & 0.3635 & 0.359772 \tabularnewline
4 & 0.147645 & 0.7081 & 0.243004 \tabularnewline
5 & 0.193328 & 0.9272 & 0.181734 \tabularnewline
6 & -0.070283 & -0.3371 & 0.369562 \tabularnewline
7 & -0.347637 & -1.6672 & 0.054517 \tabularnewline
8 & -0.157265 & -0.7542 & 0.229186 \tabularnewline
9 & -0.081222 & -0.3895 & 0.350235 \tabularnewline
10 & -0.127075 & -0.6094 & 0.274107 \tabularnewline
11 & -0.271489 & -1.302 & 0.102901 \tabularnewline
12 & -0.39739 & -1.9058 & 0.034624 \tabularnewline
13 & -0.192126 & -0.9214 & 0.183202 \tabularnewline
14 & -0.04065 & -0.195 & 0.423571 \tabularnewline
15 & 0.023744 & 0.1139 & 0.455164 \tabularnewline
16 & 0.011834 & 0.0568 & 0.477617 \tabularnewline
17 & 0.020555 & 0.0986 & 0.461163 \tabularnewline
18 & 0.026461 & 0.1269 & 0.450061 \tabularnewline
19 & 0.117577 & 0.5639 & 0.289147 \tabularnewline
20 & -0.012155 & -0.0583 & 0.477009 \tabularnewline
21 & 0.00948 & 0.0455 & 0.482064 \tabularnewline
22 & -0.054799 & -0.2628 & 0.39752 \tabularnewline
23 & NA & NA & NA \tabularnewline
24 & NA & NA & NA \tabularnewline
25 & NA & NA & NA \tabularnewline
26 & NA & NA & NA \tabularnewline
27 & NA & NA & NA \tabularnewline
28 & NA & NA & NA \tabularnewline
29 & NA & NA & NA \tabularnewline
30 & NA & NA & NA \tabularnewline
31 & NA & NA & NA \tabularnewline
32 & NA & NA & NA \tabularnewline
33 & NA & NA & NA \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60929&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]0.424074[/C][C]2.0338[/C][C]0.026833[/C][/ROW]
[ROW][C]2[/C][C]0.201595[/C][C]0.9668[/C][C]0.171846[/C][/ROW]
[ROW][C]3[/C][C]0.075797[/C][C]0.3635[/C][C]0.359772[/C][/ROW]
[ROW][C]4[/C][C]0.147645[/C][C]0.7081[/C][C]0.243004[/C][/ROW]
[ROW][C]5[/C][C]0.193328[/C][C]0.9272[/C][C]0.181734[/C][/ROW]
[ROW][C]6[/C][C]-0.070283[/C][C]-0.3371[/C][C]0.369562[/C][/ROW]
[ROW][C]7[/C][C]-0.347637[/C][C]-1.6672[/C][C]0.054517[/C][/ROW]
[ROW][C]8[/C][C]-0.157265[/C][C]-0.7542[/C][C]0.229186[/C][/ROW]
[ROW][C]9[/C][C]-0.081222[/C][C]-0.3895[/C][C]0.350235[/C][/ROW]
[ROW][C]10[/C][C]-0.127075[/C][C]-0.6094[/C][C]0.274107[/C][/ROW]
[ROW][C]11[/C][C]-0.271489[/C][C]-1.302[/C][C]0.102901[/C][/ROW]
[ROW][C]12[/C][C]-0.39739[/C][C]-1.9058[/C][C]0.034624[/C][/ROW]
[ROW][C]13[/C][C]-0.192126[/C][C]-0.9214[/C][C]0.183202[/C][/ROW]
[ROW][C]14[/C][C]-0.04065[/C][C]-0.195[/C][C]0.423571[/C][/ROW]
[ROW][C]15[/C][C]0.023744[/C][C]0.1139[/C][C]0.455164[/C][/ROW]
[ROW][C]16[/C][C]0.011834[/C][C]0.0568[/C][C]0.477617[/C][/ROW]
[ROW][C]17[/C][C]0.020555[/C][C]0.0986[/C][C]0.461163[/C][/ROW]
[ROW][C]18[/C][C]0.026461[/C][C]0.1269[/C][C]0.450061[/C][/ROW]
[ROW][C]19[/C][C]0.117577[/C][C]0.5639[/C][C]0.289147[/C][/ROW]
[ROW][C]20[/C][C]-0.012155[/C][C]-0.0583[/C][C]0.477009[/C][/ROW]
[ROW][C]21[/C][C]0.00948[/C][C]0.0455[/C][C]0.482064[/C][/ROW]
[ROW][C]22[/C][C]-0.054799[/C][C]-0.2628[/C][C]0.39752[/C][/ROW]
[ROW][C]23[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]24[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]25[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]26[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]27[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]28[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]29[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]30[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]31[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]32[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]33[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60929&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
10.4240742.03380.026833
20.2015950.96680.171846
30.0757970.36350.359772
40.1476450.70810.243004
50.1933280.92720.181734
6-0.070283-0.33710.369562
7-0.347637-1.66720.054517
8-0.157265-0.75420.229186
9-0.081222-0.38950.350235
10-0.127075-0.60940.274107
11-0.271489-1.3020.102901
12-0.39739-1.90580.034624
13-0.192126-0.92140.183202
14-0.04065-0.1950.423571
150.0237440.11390.455164
160.0118340.05680.477617
170.0205550.09860.461163
180.0264610.12690.450061
190.1175770.56390.289147
20-0.012155-0.05830.477009
210.009480.04550.482064
22-0.054799-0.26280.39752
23NANANA
24NANANA
25NANANA
26NANANA
27NANANA
28NANANA
29NANANA
30NANANA
31NANANA
32NANANA
33NANANA
34NANANA
35NANANA
36NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4240742.03380.026833
20.0265270.12720.449937
3-0.022787-0.10930.456963
40.1449390.69510.246977
50.1055910.50640.308699
6-0.26775-1.28410.105949
7-0.342401-1.64210.057087
80.1914590.91820.18402
9-0.009219-0.04420.482559
10-0.218358-1.04720.152942
11-0.09317-0.44680.329589
12-0.117123-0.56170.289875
13-0.044063-0.21130.41725
14-0.027739-0.1330.447662
150.185130.88790.191906
160.0761080.3650.359222
17-0.061-0.29250.386246
18-0.18218-0.87370.195656
19-0.022682-0.10880.457161
20-0.146032-0.70030.245368
210.0083270.03990.484244
22-0.038583-0.1850.427412
23NANANA
24NANANA
25NANANA
26NANANA
27NANANA
28NANANA
29NANANA
30NANANA
31NANANA
32NANANA
33NANANA
34NANANA
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.424074 & 2.0338 & 0.026833 \tabularnewline
2 & 0.026527 & 0.1272 & 0.449937 \tabularnewline
3 & -0.022787 & -0.1093 & 0.456963 \tabularnewline
4 & 0.144939 & 0.6951 & 0.246977 \tabularnewline
5 & 0.105591 & 0.5064 & 0.308699 \tabularnewline
6 & -0.26775 & -1.2841 & 0.105949 \tabularnewline
7 & -0.342401 & -1.6421 & 0.057087 \tabularnewline
8 & 0.191459 & 0.9182 & 0.18402 \tabularnewline
9 & -0.009219 & -0.0442 & 0.482559 \tabularnewline
10 & -0.218358 & -1.0472 & 0.152942 \tabularnewline
11 & -0.09317 & -0.4468 & 0.329589 \tabularnewline
12 & -0.117123 & -0.5617 & 0.289875 \tabularnewline
13 & -0.044063 & -0.2113 & 0.41725 \tabularnewline
14 & -0.027739 & -0.133 & 0.447662 \tabularnewline
15 & 0.18513 & 0.8879 & 0.191906 \tabularnewline
16 & 0.076108 & 0.365 & 0.359222 \tabularnewline
17 & -0.061 & -0.2925 & 0.386246 \tabularnewline
18 & -0.18218 & -0.8737 & 0.195656 \tabularnewline
19 & -0.022682 & -0.1088 & 0.457161 \tabularnewline
20 & -0.146032 & -0.7003 & 0.245368 \tabularnewline
21 & 0.008327 & 0.0399 & 0.484244 \tabularnewline
22 & -0.038583 & -0.185 & 0.427412 \tabularnewline
23 & NA & NA & NA \tabularnewline
24 & NA & NA & NA \tabularnewline
25 & NA & NA & NA \tabularnewline
26 & NA & NA & NA \tabularnewline
27 & NA & NA & NA \tabularnewline
28 & NA & NA & NA \tabularnewline
29 & NA & NA & NA \tabularnewline
30 & NA & NA & NA \tabularnewline
31 & NA & NA & NA \tabularnewline
32 & NA & NA & NA \tabularnewline
33 & NA & NA & NA \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60929&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]0.424074[/C][C]2.0338[/C][C]0.026833[/C][/ROW]
[ROW][C]2[/C][C]0.026527[/C][C]0.1272[/C][C]0.449937[/C][/ROW]
[ROW][C]3[/C][C]-0.022787[/C][C]-0.1093[/C][C]0.456963[/C][/ROW]
[ROW][C]4[/C][C]0.144939[/C][C]0.6951[/C][C]0.246977[/C][/ROW]
[ROW][C]5[/C][C]0.105591[/C][C]0.5064[/C][C]0.308699[/C][/ROW]
[ROW][C]6[/C][C]-0.26775[/C][C]-1.2841[/C][C]0.105949[/C][/ROW]
[ROW][C]7[/C][C]-0.342401[/C][C]-1.6421[/C][C]0.057087[/C][/ROW]
[ROW][C]8[/C][C]0.191459[/C][C]0.9182[/C][C]0.18402[/C][/ROW]
[ROW][C]9[/C][C]-0.009219[/C][C]-0.0442[/C][C]0.482559[/C][/ROW]
[ROW][C]10[/C][C]-0.218358[/C][C]-1.0472[/C][C]0.152942[/C][/ROW]
[ROW][C]11[/C][C]-0.09317[/C][C]-0.4468[/C][C]0.329589[/C][/ROW]
[ROW][C]12[/C][C]-0.117123[/C][C]-0.5617[/C][C]0.289875[/C][/ROW]
[ROW][C]13[/C][C]-0.044063[/C][C]-0.2113[/C][C]0.41725[/C][/ROW]
[ROW][C]14[/C][C]-0.027739[/C][C]-0.133[/C][C]0.447662[/C][/ROW]
[ROW][C]15[/C][C]0.18513[/C][C]0.8879[/C][C]0.191906[/C][/ROW]
[ROW][C]16[/C][C]0.076108[/C][C]0.365[/C][C]0.359222[/C][/ROW]
[ROW][C]17[/C][C]-0.061[/C][C]-0.2925[/C][C]0.386246[/C][/ROW]
[ROW][C]18[/C][C]-0.18218[/C][C]-0.8737[/C][C]0.195656[/C][/ROW]
[ROW][C]19[/C][C]-0.022682[/C][C]-0.1088[/C][C]0.457161[/C][/ROW]
[ROW][C]20[/C][C]-0.146032[/C][C]-0.7003[/C][C]0.245368[/C][/ROW]
[ROW][C]21[/C][C]0.008327[/C][C]0.0399[/C][C]0.484244[/C][/ROW]
[ROW][C]22[/C][C]-0.038583[/C][C]-0.185[/C][C]0.427412[/C][/ROW]
[ROW][C]23[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]24[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]25[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]26[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]27[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]28[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]29[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]30[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]31[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]32[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]33[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60929&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60929&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
10.4240742.03380.026833
20.0265270.12720.449937
3-0.022787-0.10930.456963
40.1449390.69510.246977
50.1055910.50640.308699
6-0.26775-1.28410.105949
7-0.342401-1.64210.057087
80.1914590.91820.18402
9-0.009219-0.04420.482559
10-0.218358-1.04720.152942
11-0.09317-0.44680.329589
12-0.117123-0.56170.289875
13-0.044063-0.21130.41725
14-0.027739-0.1330.447662
150.185130.88790.191906
160.0761080.3650.359222
17-0.061-0.29250.386246
18-0.18218-0.87370.195656
19-0.022682-0.10880.457161
20-0.146032-0.70030.245368
210.0083270.03990.484244
22-0.038583-0.1850.427412
23NANANA
24NANANA
25NANANA
26NANANA
27NANANA
28NANANA
29NANANA
30NANANA
31NANANA
32NANANA
33NANANA
34NANANA
35NANANA
36NANANA



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