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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 08:04:21 -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/27/t1259334306f7mythyv0bve6er.htm/, Retrieved Sun, 28 Apr 2024 22:16:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60873, Retrieved Sun, 28 Apr 2024 22:16:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-27 15:04:21] [cb3e966d7bf80cd999a0432e97d174a7] [Current]
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Dataseries X:
103,5
104,6
118,6
106,3
110,7
121,6
107
107,6
125,6
113,5
129,2
130,9
104,7
115,2
124,5
112,3
127,5
120,6
117,5
117,7
120,4
125
131,6
121,1
114,2
112,1
127
116,8
112
129,7
113,6
115,7
119,5
125,8
129,6
128
112,8
101,6
123,9
118,8
109,1
130,6
112,4
111
116,2
119,8
117,2
127,3
107,7
97,5
120,1
110,6
111,3
119,8
105,5
108,7
128,7
119,5
121,1
128,4




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=60873&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=60873&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60873&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
10.0202510.14030.444505
20.2423021.67870.049853
30.4291692.97340.002298
4-0.063189-0.43780.331752
50.2935562.03380.023759
60.193591.34120.093079
7-0.110715-0.76710.223402
80.2791471.9340.029511
90.0632270.4380.331659
10-0.096431-0.66810.253637
110.0925110.64090.262307
12-0.132164-0.91570.182211
13-0.01829-0.12670.449846
140.061180.42390.336778
15-0.052851-0.36620.357926
16-0.017487-0.12120.452039
170.0924120.64030.262527
18-0.035065-0.24290.404545
19-0.143793-0.99620.162068
200.0302220.20940.417518
21-0.044712-0.30980.379038
22-0.114269-0.79170.216222
230.1147410.79490.215279
24-0.217244-1.50510.069424
25-0.056029-0.38820.3498
26-0.017035-0.1180.453273
27-0.140653-0.97450.167354
28-0.153601-1.06420.146287
29-0.115444-0.79980.213878
30-0.196851-1.36380.089492
31-0.082679-0.57280.28472
32-0.150107-1.040.151781
33-0.202951-1.40610.08307
34-0.0621-0.43020.334472
35-0.129685-0.89850.186707
36-0.104102-0.72120.23713

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.020251 & 0.1403 & 0.444505 \tabularnewline
2 & 0.242302 & 1.6787 & 0.049853 \tabularnewline
3 & 0.429169 & 2.9734 & 0.002298 \tabularnewline
4 & -0.063189 & -0.4378 & 0.331752 \tabularnewline
5 & 0.293556 & 2.0338 & 0.023759 \tabularnewline
6 & 0.19359 & 1.3412 & 0.093079 \tabularnewline
7 & -0.110715 & -0.7671 & 0.223402 \tabularnewline
8 & 0.279147 & 1.934 & 0.029511 \tabularnewline
9 & 0.063227 & 0.438 & 0.331659 \tabularnewline
10 & -0.096431 & -0.6681 & 0.253637 \tabularnewline
11 & 0.092511 & 0.6409 & 0.262307 \tabularnewline
12 & -0.132164 & -0.9157 & 0.182211 \tabularnewline
13 & -0.01829 & -0.1267 & 0.449846 \tabularnewline
14 & 0.06118 & 0.4239 & 0.336778 \tabularnewline
15 & -0.052851 & -0.3662 & 0.357926 \tabularnewline
16 & -0.017487 & -0.1212 & 0.452039 \tabularnewline
17 & 0.092412 & 0.6403 & 0.262527 \tabularnewline
18 & -0.035065 & -0.2429 & 0.404545 \tabularnewline
19 & -0.143793 & -0.9962 & 0.162068 \tabularnewline
20 & 0.030222 & 0.2094 & 0.417518 \tabularnewline
21 & -0.044712 & -0.3098 & 0.379038 \tabularnewline
22 & -0.114269 & -0.7917 & 0.216222 \tabularnewline
23 & 0.114741 & 0.7949 & 0.215279 \tabularnewline
24 & -0.217244 & -1.5051 & 0.069424 \tabularnewline
25 & -0.056029 & -0.3882 & 0.3498 \tabularnewline
26 & -0.017035 & -0.118 & 0.453273 \tabularnewline
27 & -0.140653 & -0.9745 & 0.167354 \tabularnewline
28 & -0.153601 & -1.0642 & 0.146287 \tabularnewline
29 & -0.115444 & -0.7998 & 0.213878 \tabularnewline
30 & -0.196851 & -1.3638 & 0.089492 \tabularnewline
31 & -0.082679 & -0.5728 & 0.28472 \tabularnewline
32 & -0.150107 & -1.04 & 0.151781 \tabularnewline
33 & -0.202951 & -1.4061 & 0.08307 \tabularnewline
34 & -0.0621 & -0.4302 & 0.334472 \tabularnewline
35 & -0.129685 & -0.8985 & 0.186707 \tabularnewline
36 & -0.104102 & -0.7212 & 0.23713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60873&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]0.020251[/C][C]0.1403[/C][C]0.444505[/C][/ROW]
[ROW][C]2[/C][C]0.242302[/C][C]1.6787[/C][C]0.049853[/C][/ROW]
[ROW][C]3[/C][C]0.429169[/C][C]2.9734[/C][C]0.002298[/C][/ROW]
[ROW][C]4[/C][C]-0.063189[/C][C]-0.4378[/C][C]0.331752[/C][/ROW]
[ROW][C]5[/C][C]0.293556[/C][C]2.0338[/C][C]0.023759[/C][/ROW]
[ROW][C]6[/C][C]0.19359[/C][C]1.3412[/C][C]0.093079[/C][/ROW]
[ROW][C]7[/C][C]-0.110715[/C][C]-0.7671[/C][C]0.223402[/C][/ROW]
[ROW][C]8[/C][C]0.279147[/C][C]1.934[/C][C]0.029511[/C][/ROW]
[ROW][C]9[/C][C]0.063227[/C][C]0.438[/C][C]0.331659[/C][/ROW]
[ROW][C]10[/C][C]-0.096431[/C][C]-0.6681[/C][C]0.253637[/C][/ROW]
[ROW][C]11[/C][C]0.092511[/C][C]0.6409[/C][C]0.262307[/C][/ROW]
[ROW][C]12[/C][C]-0.132164[/C][C]-0.9157[/C][C]0.182211[/C][/ROW]
[ROW][C]13[/C][C]-0.01829[/C][C]-0.1267[/C][C]0.449846[/C][/ROW]
[ROW][C]14[/C][C]0.06118[/C][C]0.4239[/C][C]0.336778[/C][/ROW]
[ROW][C]15[/C][C]-0.052851[/C][C]-0.3662[/C][C]0.357926[/C][/ROW]
[ROW][C]16[/C][C]-0.017487[/C][C]-0.1212[/C][C]0.452039[/C][/ROW]
[ROW][C]17[/C][C]0.092412[/C][C]0.6403[/C][C]0.262527[/C][/ROW]
[ROW][C]18[/C][C]-0.035065[/C][C]-0.2429[/C][C]0.404545[/C][/ROW]
[ROW][C]19[/C][C]-0.143793[/C][C]-0.9962[/C][C]0.162068[/C][/ROW]
[ROW][C]20[/C][C]0.030222[/C][C]0.2094[/C][C]0.417518[/C][/ROW]
[ROW][C]21[/C][C]-0.044712[/C][C]-0.3098[/C][C]0.379038[/C][/ROW]
[ROW][C]22[/C][C]-0.114269[/C][C]-0.7917[/C][C]0.216222[/C][/ROW]
[ROW][C]23[/C][C]0.114741[/C][C]0.7949[/C][C]0.215279[/C][/ROW]
[ROW][C]24[/C][C]-0.217244[/C][C]-1.5051[/C][C]0.069424[/C][/ROW]
[ROW][C]25[/C][C]-0.056029[/C][C]-0.3882[/C][C]0.3498[/C][/ROW]
[ROW][C]26[/C][C]-0.017035[/C][C]-0.118[/C][C]0.453273[/C][/ROW]
[ROW][C]27[/C][C]-0.140653[/C][C]-0.9745[/C][C]0.167354[/C][/ROW]
[ROW][C]28[/C][C]-0.153601[/C][C]-1.0642[/C][C]0.146287[/C][/ROW]
[ROW][C]29[/C][C]-0.115444[/C][C]-0.7998[/C][C]0.213878[/C][/ROW]
[ROW][C]30[/C][C]-0.196851[/C][C]-1.3638[/C][C]0.089492[/C][/ROW]
[ROW][C]31[/C][C]-0.082679[/C][C]-0.5728[/C][C]0.28472[/C][/ROW]
[ROW][C]32[/C][C]-0.150107[/C][C]-1.04[/C][C]0.151781[/C][/ROW]
[ROW][C]33[/C][C]-0.202951[/C][C]-1.4061[/C][C]0.08307[/C][/ROW]
[ROW][C]34[/C][C]-0.0621[/C][C]-0.4302[/C][C]0.334472[/C][/ROW]
[ROW][C]35[/C][C]-0.129685[/C][C]-0.8985[/C][C]0.186707[/C][/ROW]
[ROW][C]36[/C][C]-0.104102[/C][C]-0.7212[/C][C]0.23713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60873&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60873&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
10.0202510.14030.444505
20.2423021.67870.049853
30.4291692.97340.002298
4-0.063189-0.43780.331752
50.2935562.03380.023759
60.193591.34120.093079
7-0.110715-0.76710.223402
80.2791471.9340.029511
90.0632270.4380.331659
10-0.096431-0.66810.253637
110.0925110.64090.262307
12-0.132164-0.91570.182211
13-0.01829-0.12670.449846
140.061180.42390.336778
15-0.052851-0.36620.357926
16-0.017487-0.12120.452039
170.0924120.64030.262527
18-0.035065-0.24290.404545
19-0.143793-0.99620.162068
200.0302220.20940.417518
21-0.044712-0.30980.379038
22-0.114269-0.79170.216222
230.1147410.79490.215279
24-0.217244-1.50510.069424
25-0.056029-0.38820.3498
26-0.017035-0.1180.453273
27-0.140653-0.97450.167354
28-0.153601-1.06420.146287
29-0.115444-0.79980.213878
30-0.196851-1.36380.089492
31-0.082679-0.57280.28472
32-0.150107-1.040.151781
33-0.202951-1.40610.08307
34-0.0621-0.43020.334472
35-0.129685-0.89850.186707
36-0.104102-0.72120.23713







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0202510.14030.444505
20.2419911.67660.050065
30.4468913.09620.001635
4-0.118691-0.82230.207482
50.1009360.69930.243868
60.0893350.61890.269444
7-0.15993-1.1080.136686
80.062110.43030.334449
90.0889810.61650.270247
10-0.124791-0.86460.195785
11-0.179472-1.24340.109876
12-0.087997-0.60970.272481
130.0663350.45960.323947
140.0531590.36830.357136
150.1293670.89630.187288
16-0.022159-0.15350.439315
170.0638330.44230.330147
180.0175950.12190.451743
19-0.255585-1.77070.041476
20-0.041296-0.28610.388013
210.1218670.84430.20134
22-0.102477-0.710.240575
230.0291230.20180.420474
24-0.129502-0.89720.187041
25-0.047956-0.33220.370574
26-0.108053-0.74860.228871
270.2162961.49850.070271
28-0.152655-1.05760.147761
29-0.176457-1.22250.113738
30-0.075066-0.52010.302702
31-0.044759-0.31010.378913
32-0.064172-0.44460.329304
330.0417960.28960.386697
340.0687560.47640.317992
35-0.026674-0.18480.427081
360.0045750.03170.487422

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.020251 & 0.1403 & 0.444505 \tabularnewline
2 & 0.241991 & 1.6766 & 0.050065 \tabularnewline
3 & 0.446891 & 3.0962 & 0.001635 \tabularnewline
4 & -0.118691 & -0.8223 & 0.207482 \tabularnewline
5 & 0.100936 & 0.6993 & 0.243868 \tabularnewline
6 & 0.089335 & 0.6189 & 0.269444 \tabularnewline
7 & -0.15993 & -1.108 & 0.136686 \tabularnewline
8 & 0.06211 & 0.4303 & 0.334449 \tabularnewline
9 & 0.088981 & 0.6165 & 0.270247 \tabularnewline
10 & -0.124791 & -0.8646 & 0.195785 \tabularnewline
11 & -0.179472 & -1.2434 & 0.109876 \tabularnewline
12 & -0.087997 & -0.6097 & 0.272481 \tabularnewline
13 & 0.066335 & 0.4596 & 0.323947 \tabularnewline
14 & 0.053159 & 0.3683 & 0.357136 \tabularnewline
15 & 0.129367 & 0.8963 & 0.187288 \tabularnewline
16 & -0.022159 & -0.1535 & 0.439315 \tabularnewline
17 & 0.063833 & 0.4423 & 0.330147 \tabularnewline
18 & 0.017595 & 0.1219 & 0.451743 \tabularnewline
19 & -0.255585 & -1.7707 & 0.041476 \tabularnewline
20 & -0.041296 & -0.2861 & 0.388013 \tabularnewline
21 & 0.121867 & 0.8443 & 0.20134 \tabularnewline
22 & -0.102477 & -0.71 & 0.240575 \tabularnewline
23 & 0.029123 & 0.2018 & 0.420474 \tabularnewline
24 & -0.129502 & -0.8972 & 0.187041 \tabularnewline
25 & -0.047956 & -0.3322 & 0.370574 \tabularnewline
26 & -0.108053 & -0.7486 & 0.228871 \tabularnewline
27 & 0.216296 & 1.4985 & 0.070271 \tabularnewline
28 & -0.152655 & -1.0576 & 0.147761 \tabularnewline
29 & -0.176457 & -1.2225 & 0.113738 \tabularnewline
30 & -0.075066 & -0.5201 & 0.302702 \tabularnewline
31 & -0.044759 & -0.3101 & 0.378913 \tabularnewline
32 & -0.064172 & -0.4446 & 0.329304 \tabularnewline
33 & 0.041796 & 0.2896 & 0.386697 \tabularnewline
34 & 0.068756 & 0.4764 & 0.317992 \tabularnewline
35 & -0.026674 & -0.1848 & 0.427081 \tabularnewline
36 & 0.004575 & 0.0317 & 0.487422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60873&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]0.020251[/C][C]0.1403[/C][C]0.444505[/C][/ROW]
[ROW][C]2[/C][C]0.241991[/C][C]1.6766[/C][C]0.050065[/C][/ROW]
[ROW][C]3[/C][C]0.446891[/C][C]3.0962[/C][C]0.001635[/C][/ROW]
[ROW][C]4[/C][C]-0.118691[/C][C]-0.8223[/C][C]0.207482[/C][/ROW]
[ROW][C]5[/C][C]0.100936[/C][C]0.6993[/C][C]0.243868[/C][/ROW]
[ROW][C]6[/C][C]0.089335[/C][C]0.6189[/C][C]0.269444[/C][/ROW]
[ROW][C]7[/C][C]-0.15993[/C][C]-1.108[/C][C]0.136686[/C][/ROW]
[ROW][C]8[/C][C]0.06211[/C][C]0.4303[/C][C]0.334449[/C][/ROW]
[ROW][C]9[/C][C]0.088981[/C][C]0.6165[/C][C]0.270247[/C][/ROW]
[ROW][C]10[/C][C]-0.124791[/C][C]-0.8646[/C][C]0.195785[/C][/ROW]
[ROW][C]11[/C][C]-0.179472[/C][C]-1.2434[/C][C]0.109876[/C][/ROW]
[ROW][C]12[/C][C]-0.087997[/C][C]-0.6097[/C][C]0.272481[/C][/ROW]
[ROW][C]13[/C][C]0.066335[/C][C]0.4596[/C][C]0.323947[/C][/ROW]
[ROW][C]14[/C][C]0.053159[/C][C]0.3683[/C][C]0.357136[/C][/ROW]
[ROW][C]15[/C][C]0.129367[/C][C]0.8963[/C][C]0.187288[/C][/ROW]
[ROW][C]16[/C][C]-0.022159[/C][C]-0.1535[/C][C]0.439315[/C][/ROW]
[ROW][C]17[/C][C]0.063833[/C][C]0.4423[/C][C]0.330147[/C][/ROW]
[ROW][C]18[/C][C]0.017595[/C][C]0.1219[/C][C]0.451743[/C][/ROW]
[ROW][C]19[/C][C]-0.255585[/C][C]-1.7707[/C][C]0.041476[/C][/ROW]
[ROW][C]20[/C][C]-0.041296[/C][C]-0.2861[/C][C]0.388013[/C][/ROW]
[ROW][C]21[/C][C]0.121867[/C][C]0.8443[/C][C]0.20134[/C][/ROW]
[ROW][C]22[/C][C]-0.102477[/C][C]-0.71[/C][C]0.240575[/C][/ROW]
[ROW][C]23[/C][C]0.029123[/C][C]0.2018[/C][C]0.420474[/C][/ROW]
[ROW][C]24[/C][C]-0.129502[/C][C]-0.8972[/C][C]0.187041[/C][/ROW]
[ROW][C]25[/C][C]-0.047956[/C][C]-0.3322[/C][C]0.370574[/C][/ROW]
[ROW][C]26[/C][C]-0.108053[/C][C]-0.7486[/C][C]0.228871[/C][/ROW]
[ROW][C]27[/C][C]0.216296[/C][C]1.4985[/C][C]0.070271[/C][/ROW]
[ROW][C]28[/C][C]-0.152655[/C][C]-1.0576[/C][C]0.147761[/C][/ROW]
[ROW][C]29[/C][C]-0.176457[/C][C]-1.2225[/C][C]0.113738[/C][/ROW]
[ROW][C]30[/C][C]-0.075066[/C][C]-0.5201[/C][C]0.302702[/C][/ROW]
[ROW][C]31[/C][C]-0.044759[/C][C]-0.3101[/C][C]0.378913[/C][/ROW]
[ROW][C]32[/C][C]-0.064172[/C][C]-0.4446[/C][C]0.329304[/C][/ROW]
[ROW][C]33[/C][C]0.041796[/C][C]0.2896[/C][C]0.386697[/C][/ROW]
[ROW][C]34[/C][C]0.068756[/C][C]0.4764[/C][C]0.317992[/C][/ROW]
[ROW][C]35[/C][C]-0.026674[/C][C]-0.1848[/C][C]0.427081[/C][/ROW]
[ROW][C]36[/C][C]0.004575[/C][C]0.0317[/C][C]0.487422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60873&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60873&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
10.0202510.14030.444505
20.2419911.67660.050065
30.4468913.09620.001635
4-0.118691-0.82230.207482
50.1009360.69930.243868
60.0893350.61890.269444
7-0.15993-1.1080.136686
80.062110.43030.334449
90.0889810.61650.270247
10-0.124791-0.86460.195785
11-0.179472-1.24340.109876
12-0.087997-0.60970.272481
130.0663350.45960.323947
140.0531590.36830.357136
150.1293670.89630.187288
16-0.022159-0.15350.439315
170.0638330.44230.330147
180.0175950.12190.451743
19-0.255585-1.77070.041476
20-0.041296-0.28610.388013
210.1218670.84430.20134
22-0.102477-0.710.240575
230.0291230.20180.420474
24-0.129502-0.89720.187041
25-0.047956-0.33220.370574
26-0.108053-0.74860.228871
270.2162961.49850.070271
28-0.152655-1.05760.147761
29-0.176457-1.22250.113738
30-0.075066-0.52010.302702
31-0.044759-0.31010.378913
32-0.064172-0.44460.329304
330.0417960.28960.386697
340.0687560.47640.317992
35-0.026674-0.18480.427081
360.0045750.03170.487422



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