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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, 18 Dec 2009 02:23:37 -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/18/t1261128270hi9jg68ded4hs99.htm/, Retrieved Sat, 27 Apr 2024 09:10:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69178, Retrieved Sat, 27 Apr 2024 09:10:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
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] [] [2009-12-18 09:23:37] [54f12ba6dfaf5b88c7c2745223d9c32f] [Current]
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Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971




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=69178&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=69178&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69178&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
10.5176243.58620.000392
20.5873434.06928.7e-05
30.3469782.40390.010065
40.2323331.60960.057016
50.1166030.80780.211582
60.1201120.83220.204719
7-0.04162-0.28840.387159
80.0020960.01450.494236
9-0.16762-1.16130.12563
10-0.212705-1.47370.07355
11-0.261613-1.81250.038082
12-0.376378-2.60760.006057
13-0.351845-2.43770.009269
14-0.307357-2.12940.019187
15-0.198272-1.37370.087963
16-0.177801-1.23180.112005
17-0.082956-0.57470.284078
18-0.095832-0.66390.254951
19-0.048511-0.33610.369132
20-0.032322-0.22390.411879
210.0873140.60490.274038
22-0.025866-0.17920.429264
230.1760971.220.114206
240.0631030.43720.331967
250.1819651.26070.106757
260.1573711.09030.140512
270.124580.86310.196184
280.0138240.09580.462048
290.0499990.34640.365276
30-0.082779-0.57350.284489
31-0.017879-0.12390.450969
32-0.095042-0.65850.256691
33-0.124937-0.86560.195511
34-0.095386-0.66090.255933
35-0.155304-1.0760.143657
36-0.147016-1.01860.156761

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.517624 & 3.5862 & 0.000392 \tabularnewline
2 & 0.587343 & 4.0692 & 8.7e-05 \tabularnewline
3 & 0.346978 & 2.4039 & 0.010065 \tabularnewline
4 & 0.232333 & 1.6096 & 0.057016 \tabularnewline
5 & 0.116603 & 0.8078 & 0.211582 \tabularnewline
6 & 0.120112 & 0.8322 & 0.204719 \tabularnewline
7 & -0.04162 & -0.2884 & 0.387159 \tabularnewline
8 & 0.002096 & 0.0145 & 0.494236 \tabularnewline
9 & -0.16762 & -1.1613 & 0.12563 \tabularnewline
10 & -0.212705 & -1.4737 & 0.07355 \tabularnewline
11 & -0.261613 & -1.8125 & 0.038082 \tabularnewline
12 & -0.376378 & -2.6076 & 0.006057 \tabularnewline
13 & -0.351845 & -2.4377 & 0.009269 \tabularnewline
14 & -0.307357 & -2.1294 & 0.019187 \tabularnewline
15 & -0.198272 & -1.3737 & 0.087963 \tabularnewline
16 & -0.177801 & -1.2318 & 0.112005 \tabularnewline
17 & -0.082956 & -0.5747 & 0.284078 \tabularnewline
18 & -0.095832 & -0.6639 & 0.254951 \tabularnewline
19 & -0.048511 & -0.3361 & 0.369132 \tabularnewline
20 & -0.032322 & -0.2239 & 0.411879 \tabularnewline
21 & 0.087314 & 0.6049 & 0.274038 \tabularnewline
22 & -0.025866 & -0.1792 & 0.429264 \tabularnewline
23 & 0.176097 & 1.22 & 0.114206 \tabularnewline
24 & 0.063103 & 0.4372 & 0.331967 \tabularnewline
25 & 0.181965 & 1.2607 & 0.106757 \tabularnewline
26 & 0.157371 & 1.0903 & 0.140512 \tabularnewline
27 & 0.12458 & 0.8631 & 0.196184 \tabularnewline
28 & 0.013824 & 0.0958 & 0.462048 \tabularnewline
29 & 0.049999 & 0.3464 & 0.365276 \tabularnewline
30 & -0.082779 & -0.5735 & 0.284489 \tabularnewline
31 & -0.017879 & -0.1239 & 0.450969 \tabularnewline
32 & -0.095042 & -0.6585 & 0.256691 \tabularnewline
33 & -0.124937 & -0.8656 & 0.195511 \tabularnewline
34 & -0.095386 & -0.6609 & 0.255933 \tabularnewline
35 & -0.155304 & -1.076 & 0.143657 \tabularnewline
36 & -0.147016 & -1.0186 & 0.156761 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69178&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]0.517624[/C][C]3.5862[/C][C]0.000392[/C][/ROW]
[ROW][C]2[/C][C]0.587343[/C][C]4.0692[/C][C]8.7e-05[/C][/ROW]
[ROW][C]3[/C][C]0.346978[/C][C]2.4039[/C][C]0.010065[/C][/ROW]
[ROW][C]4[/C][C]0.232333[/C][C]1.6096[/C][C]0.057016[/C][/ROW]
[ROW][C]5[/C][C]0.116603[/C][C]0.8078[/C][C]0.211582[/C][/ROW]
[ROW][C]6[/C][C]0.120112[/C][C]0.8322[/C][C]0.204719[/C][/ROW]
[ROW][C]7[/C][C]-0.04162[/C][C]-0.2884[/C][C]0.387159[/C][/ROW]
[ROW][C]8[/C][C]0.002096[/C][C]0.0145[/C][C]0.494236[/C][/ROW]
[ROW][C]9[/C][C]-0.16762[/C][C]-1.1613[/C][C]0.12563[/C][/ROW]
[ROW][C]10[/C][C]-0.212705[/C][C]-1.4737[/C][C]0.07355[/C][/ROW]
[ROW][C]11[/C][C]-0.261613[/C][C]-1.8125[/C][C]0.038082[/C][/ROW]
[ROW][C]12[/C][C]-0.376378[/C][C]-2.6076[/C][C]0.006057[/C][/ROW]
[ROW][C]13[/C][C]-0.351845[/C][C]-2.4377[/C][C]0.009269[/C][/ROW]
[ROW][C]14[/C][C]-0.307357[/C][C]-2.1294[/C][C]0.019187[/C][/ROW]
[ROW][C]15[/C][C]-0.198272[/C][C]-1.3737[/C][C]0.087963[/C][/ROW]
[ROW][C]16[/C][C]-0.177801[/C][C]-1.2318[/C][C]0.112005[/C][/ROW]
[ROW][C]17[/C][C]-0.082956[/C][C]-0.5747[/C][C]0.284078[/C][/ROW]
[ROW][C]18[/C][C]-0.095832[/C][C]-0.6639[/C][C]0.254951[/C][/ROW]
[ROW][C]19[/C][C]-0.048511[/C][C]-0.3361[/C][C]0.369132[/C][/ROW]
[ROW][C]20[/C][C]-0.032322[/C][C]-0.2239[/C][C]0.411879[/C][/ROW]
[ROW][C]21[/C][C]0.087314[/C][C]0.6049[/C][C]0.274038[/C][/ROW]
[ROW][C]22[/C][C]-0.025866[/C][C]-0.1792[/C][C]0.429264[/C][/ROW]
[ROW][C]23[/C][C]0.176097[/C][C]1.22[/C][C]0.114206[/C][/ROW]
[ROW][C]24[/C][C]0.063103[/C][C]0.4372[/C][C]0.331967[/C][/ROW]
[ROW][C]25[/C][C]0.181965[/C][C]1.2607[/C][C]0.106757[/C][/ROW]
[ROW][C]26[/C][C]0.157371[/C][C]1.0903[/C][C]0.140512[/C][/ROW]
[ROW][C]27[/C][C]0.12458[/C][C]0.8631[/C][C]0.196184[/C][/ROW]
[ROW][C]28[/C][C]0.013824[/C][C]0.0958[/C][C]0.462048[/C][/ROW]
[ROW][C]29[/C][C]0.049999[/C][C]0.3464[/C][C]0.365276[/C][/ROW]
[ROW][C]30[/C][C]-0.082779[/C][C]-0.5735[/C][C]0.284489[/C][/ROW]
[ROW][C]31[/C][C]-0.017879[/C][C]-0.1239[/C][C]0.450969[/C][/ROW]
[ROW][C]32[/C][C]-0.095042[/C][C]-0.6585[/C][C]0.256691[/C][/ROW]
[ROW][C]33[/C][C]-0.124937[/C][C]-0.8656[/C][C]0.195511[/C][/ROW]
[ROW][C]34[/C][C]-0.095386[/C][C]-0.6609[/C][C]0.255933[/C][/ROW]
[ROW][C]35[/C][C]-0.155304[/C][C]-1.076[/C][C]0.143657[/C][/ROW]
[ROW][C]36[/C][C]-0.147016[/C][C]-1.0186[/C][C]0.156761[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69178&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69178&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
10.5176243.58620.000392
20.5873434.06928.7e-05
30.3469782.40390.010065
40.2323331.60960.057016
50.1166030.80780.211582
60.1201120.83220.204719
7-0.04162-0.28840.387159
80.0020960.01450.494236
9-0.16762-1.16130.12563
10-0.212705-1.47370.07355
11-0.261613-1.81250.038082
12-0.376378-2.60760.006057
13-0.351845-2.43770.009269
14-0.307357-2.12940.019187
15-0.198272-1.37370.087963
16-0.177801-1.23180.112005
17-0.082956-0.57470.284078
18-0.095832-0.66390.254951
19-0.048511-0.33610.369132
20-0.032322-0.22390.411879
210.0873140.60490.274038
22-0.025866-0.17920.429264
230.1760971.220.114206
240.0631030.43720.331967
250.1819651.26070.106757
260.1573711.09030.140512
270.124580.86310.196184
280.0138240.09580.462048
290.0499990.34640.365276
30-0.082779-0.57350.284489
31-0.017879-0.12390.450969
32-0.095042-0.65850.256691
33-0.124937-0.86560.195511
34-0.095386-0.66090.255933
35-0.155304-1.0760.143657
36-0.147016-1.01860.156761







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5176243.58620.000392
20.4363123.02290.002005
3-0.084765-0.58730.279887
4-0.184648-1.27930.103474
5-0.06324-0.43810.331626
60.1489881.03220.153571
7-0.136658-0.94680.174244
8-0.040775-0.28250.389389
9-0.157909-1.0940.139702
10-0.154778-1.07230.144466
11-0.016045-0.11120.455974
12-0.181284-1.2560.107603
13-0.049852-0.34540.365658
140.0817980.56670.286775
150.2119331.46830.074271
16-0.085167-0.59010.278962
17-0.082114-0.56890.286036
18-0.005285-0.03660.485471
19-0.004029-0.02790.488924
200.0284490.19710.422291
210.1159250.80320.212922
22-0.26498-1.83580.03629
230.0970880.67260.2522
240.0314510.21790.414216
250.0296210.20520.419135
260.0207120.14350.443249
27-0.063409-0.43930.331205
28-0.164796-1.14170.129613
290.0082840.05740.477235
300.0508650.35240.36304
31-0.06755-0.4680.320952
32-0.09872-0.6840.248646
33-0.019691-0.13640.446028
340.0599590.41540.339847
35-0.042029-0.29120.386083
36-0.05577-0.38640.350459

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.517624 & 3.5862 & 0.000392 \tabularnewline
2 & 0.436312 & 3.0229 & 0.002005 \tabularnewline
3 & -0.084765 & -0.5873 & 0.279887 \tabularnewline
4 & -0.184648 & -1.2793 & 0.103474 \tabularnewline
5 & -0.06324 & -0.4381 & 0.331626 \tabularnewline
6 & 0.148988 & 1.0322 & 0.153571 \tabularnewline
7 & -0.136658 & -0.9468 & 0.174244 \tabularnewline
8 & -0.040775 & -0.2825 & 0.389389 \tabularnewline
9 & -0.157909 & -1.094 & 0.139702 \tabularnewline
10 & -0.154778 & -1.0723 & 0.144466 \tabularnewline
11 & -0.016045 & -0.1112 & 0.455974 \tabularnewline
12 & -0.181284 & -1.256 & 0.107603 \tabularnewline
13 & -0.049852 & -0.3454 & 0.365658 \tabularnewline
14 & 0.081798 & 0.5667 & 0.286775 \tabularnewline
15 & 0.211933 & 1.4683 & 0.074271 \tabularnewline
16 & -0.085167 & -0.5901 & 0.278962 \tabularnewline
17 & -0.082114 & -0.5689 & 0.286036 \tabularnewline
18 & -0.005285 & -0.0366 & 0.485471 \tabularnewline
19 & -0.004029 & -0.0279 & 0.488924 \tabularnewline
20 & 0.028449 & 0.1971 & 0.422291 \tabularnewline
21 & 0.115925 & 0.8032 & 0.212922 \tabularnewline
22 & -0.26498 & -1.8358 & 0.03629 \tabularnewline
23 & 0.097088 & 0.6726 & 0.2522 \tabularnewline
24 & 0.031451 & 0.2179 & 0.414216 \tabularnewline
25 & 0.029621 & 0.2052 & 0.419135 \tabularnewline
26 & 0.020712 & 0.1435 & 0.443249 \tabularnewline
27 & -0.063409 & -0.4393 & 0.331205 \tabularnewline
28 & -0.164796 & -1.1417 & 0.129613 \tabularnewline
29 & 0.008284 & 0.0574 & 0.477235 \tabularnewline
30 & 0.050865 & 0.3524 & 0.36304 \tabularnewline
31 & -0.06755 & -0.468 & 0.320952 \tabularnewline
32 & -0.09872 & -0.684 & 0.248646 \tabularnewline
33 & -0.019691 & -0.1364 & 0.446028 \tabularnewline
34 & 0.059959 & 0.4154 & 0.339847 \tabularnewline
35 & -0.042029 & -0.2912 & 0.386083 \tabularnewline
36 & -0.05577 & -0.3864 & 0.350459 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69178&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]0.517624[/C][C]3.5862[/C][C]0.000392[/C][/ROW]
[ROW][C]2[/C][C]0.436312[/C][C]3.0229[/C][C]0.002005[/C][/ROW]
[ROW][C]3[/C][C]-0.084765[/C][C]-0.5873[/C][C]0.279887[/C][/ROW]
[ROW][C]4[/C][C]-0.184648[/C][C]-1.2793[/C][C]0.103474[/C][/ROW]
[ROW][C]5[/C][C]-0.06324[/C][C]-0.4381[/C][C]0.331626[/C][/ROW]
[ROW][C]6[/C][C]0.148988[/C][C]1.0322[/C][C]0.153571[/C][/ROW]
[ROW][C]7[/C][C]-0.136658[/C][C]-0.9468[/C][C]0.174244[/C][/ROW]
[ROW][C]8[/C][C]-0.040775[/C][C]-0.2825[/C][C]0.389389[/C][/ROW]
[ROW][C]9[/C][C]-0.157909[/C][C]-1.094[/C][C]0.139702[/C][/ROW]
[ROW][C]10[/C][C]-0.154778[/C][C]-1.0723[/C][C]0.144466[/C][/ROW]
[ROW][C]11[/C][C]-0.016045[/C][C]-0.1112[/C][C]0.455974[/C][/ROW]
[ROW][C]12[/C][C]-0.181284[/C][C]-1.256[/C][C]0.107603[/C][/ROW]
[ROW][C]13[/C][C]-0.049852[/C][C]-0.3454[/C][C]0.365658[/C][/ROW]
[ROW][C]14[/C][C]0.081798[/C][C]0.5667[/C][C]0.286775[/C][/ROW]
[ROW][C]15[/C][C]0.211933[/C][C]1.4683[/C][C]0.074271[/C][/ROW]
[ROW][C]16[/C][C]-0.085167[/C][C]-0.5901[/C][C]0.278962[/C][/ROW]
[ROW][C]17[/C][C]-0.082114[/C][C]-0.5689[/C][C]0.286036[/C][/ROW]
[ROW][C]18[/C][C]-0.005285[/C][C]-0.0366[/C][C]0.485471[/C][/ROW]
[ROW][C]19[/C][C]-0.004029[/C][C]-0.0279[/C][C]0.488924[/C][/ROW]
[ROW][C]20[/C][C]0.028449[/C][C]0.1971[/C][C]0.422291[/C][/ROW]
[ROW][C]21[/C][C]0.115925[/C][C]0.8032[/C][C]0.212922[/C][/ROW]
[ROW][C]22[/C][C]-0.26498[/C][C]-1.8358[/C][C]0.03629[/C][/ROW]
[ROW][C]23[/C][C]0.097088[/C][C]0.6726[/C][C]0.2522[/C][/ROW]
[ROW][C]24[/C][C]0.031451[/C][C]0.2179[/C][C]0.414216[/C][/ROW]
[ROW][C]25[/C][C]0.029621[/C][C]0.2052[/C][C]0.419135[/C][/ROW]
[ROW][C]26[/C][C]0.020712[/C][C]0.1435[/C][C]0.443249[/C][/ROW]
[ROW][C]27[/C][C]-0.063409[/C][C]-0.4393[/C][C]0.331205[/C][/ROW]
[ROW][C]28[/C][C]-0.164796[/C][C]-1.1417[/C][C]0.129613[/C][/ROW]
[ROW][C]29[/C][C]0.008284[/C][C]0.0574[/C][C]0.477235[/C][/ROW]
[ROW][C]30[/C][C]0.050865[/C][C]0.3524[/C][C]0.36304[/C][/ROW]
[ROW][C]31[/C][C]-0.06755[/C][C]-0.468[/C][C]0.320952[/C][/ROW]
[ROW][C]32[/C][C]-0.09872[/C][C]-0.684[/C][C]0.248646[/C][/ROW]
[ROW][C]33[/C][C]-0.019691[/C][C]-0.1364[/C][C]0.446028[/C][/ROW]
[ROW][C]34[/C][C]0.059959[/C][C]0.4154[/C][C]0.339847[/C][/ROW]
[ROW][C]35[/C][C]-0.042029[/C][C]-0.2912[/C][C]0.386083[/C][/ROW]
[ROW][C]36[/C][C]-0.05577[/C][C]-0.3864[/C][C]0.350459[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69178&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69178&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
10.5176243.58620.000392
20.4363123.02290.002005
3-0.084765-0.58730.279887
4-0.184648-1.27930.103474
5-0.06324-0.43810.331626
60.1489881.03220.153571
7-0.136658-0.94680.174244
8-0.040775-0.28250.389389
9-0.157909-1.0940.139702
10-0.154778-1.07230.144466
11-0.016045-0.11120.455974
12-0.181284-1.2560.107603
13-0.049852-0.34540.365658
140.0817980.56670.286775
150.2119331.46830.074271
16-0.085167-0.59010.278962
17-0.082114-0.56890.286036
18-0.005285-0.03660.485471
19-0.004029-0.02790.488924
200.0284490.19710.422291
210.1159250.80320.212922
22-0.26498-1.83580.03629
230.0970880.67260.2522
240.0314510.21790.414216
250.0296210.20520.419135
260.0207120.14350.443249
27-0.063409-0.43930.331205
28-0.164796-1.14170.129613
290.0082840.05740.477235
300.0508650.35240.36304
31-0.06755-0.4680.320952
32-0.09872-0.6840.248646
33-0.019691-0.13640.446028
340.0599590.41540.339847
35-0.042029-0.29120.386083
36-0.05577-0.38640.350459



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')