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Description of Statistical Computation

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, 17 Dec 2009 05:59:08 -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/17/t1261054814lu6s0zh7rw4giac.htm/, Retrieved Tue, 30 Apr 2024 03:34:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68839, Retrieved Tue, 30 Apr 2024 03:34:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHW Paper: (Partial) Autocorrelation function
Estimated Impact205

Tree of Dependent Computations

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]
-    D        [(Partial) Autocorrelation Function] [WS 8 Methode 1: A...] [2009-11-25 13:07:25] [b103a1dc147def8132c7f643ad8c8f84]
-    D            [(Partial) Autocorrelation Function] [Paper: (Partial) ...] [2009-12-17 12:59:08] [a45cc820faa25ce30779915639528ec2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15.5
15.1
11.7
16.3
16.7
15
14.9
14.6
15.3
17.9
16.4
15.4
17.9
15.9
13.9
17.8
17.9
17.4
16.7
16
16.6
19.1
17.8
17.2
18.6
16.3
15.1
19.2
17.7
19.1
18
17.5
17.8
21.1
17.2
19.4
19.8
17.6
16.2
19.5
19.9
20
17.3
18.9
18.6
21.4
18.6
19.8
20.8
19.6
17.7
19.8
22.2
20.7
17.9
20.9
21.2
21.4
23
21.3
23.9
22.4
18.3
22.8
22.3
17.8
16.4
16
16.4
17.7
16.6
16.2
18.3

Tables (Output of Computation)





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=68839&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=68839&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68839&T=0

As an alternative you can also use a QR Code:  
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
1-0.56813-4.40072.3e-05
20.0623780.48320.315364
30.3797262.94130.002319
4-0.345198-2.67390.004823
50.1237560.95860.170802
60.1926821.49250.070402
7-0.385237-2.9840.002055
80.2978062.30680.012267
9-0.09298-0.72020.237092
10-0.104311-0.8080.211143
110.1339061.03720.151895
12-0.085221-0.66010.255853
13-0.015797-0.12240.451509
140.0490470.37990.352676
150.0411220.31850.375596
16-0.173855-1.34670.091575
170.1596891.23690.110463
18-0.074326-0.57570.283478
19-0.073724-0.57110.285045
200.1327781.02850.153922
21-0.038708-0.29980.382671
22-0.219262-1.69840.047307
230.4047043.13480.001331
24-0.345349-2.67510.004808
250.0957250.74150.230647
260.1297781.00530.159405
27-0.178787-1.38490.085609
280.0634460.49140.312452
290.101650.78740.217081
30-0.18463-1.43010.078933
310.1396881.0820.141786
32-0.066874-0.5180.30318
33-0.001669-0.01290.494863
340.045310.3510.363421
35-0.077296-0.59870.275804
360.0107370.08320.466997

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.56813 & -4.4007 & 2.3e-05 \tabularnewline
2 & 0.062378 & 0.4832 & 0.315364 \tabularnewline
3 & 0.379726 & 2.9413 & 0.002319 \tabularnewline
4 & -0.345198 & -2.6739 & 0.004823 \tabularnewline
5 & 0.123756 & 0.9586 & 0.170802 \tabularnewline
6 & 0.192682 & 1.4925 & 0.070402 \tabularnewline
7 & -0.385237 & -2.984 & 0.002055 \tabularnewline
8 & 0.297806 & 2.3068 & 0.012267 \tabularnewline
9 & -0.09298 & -0.7202 & 0.237092 \tabularnewline
10 & -0.104311 & -0.808 & 0.211143 \tabularnewline
11 & 0.133906 & 1.0372 & 0.151895 \tabularnewline
12 & -0.085221 & -0.6601 & 0.255853 \tabularnewline
13 & -0.015797 & -0.1224 & 0.451509 \tabularnewline
14 & 0.049047 & 0.3799 & 0.352676 \tabularnewline
15 & 0.041122 & 0.3185 & 0.375596 \tabularnewline
16 & -0.173855 & -1.3467 & 0.091575 \tabularnewline
17 & 0.159689 & 1.2369 & 0.110463 \tabularnewline
18 & -0.074326 & -0.5757 & 0.283478 \tabularnewline
19 & -0.073724 & -0.5711 & 0.285045 \tabularnewline
20 & 0.132778 & 1.0285 & 0.153922 \tabularnewline
21 & -0.038708 & -0.2998 & 0.382671 \tabularnewline
22 & -0.219262 & -1.6984 & 0.047307 \tabularnewline
23 & 0.404704 & 3.1348 & 0.001331 \tabularnewline
24 & -0.345349 & -2.6751 & 0.004808 \tabularnewline
25 & 0.095725 & 0.7415 & 0.230647 \tabularnewline
26 & 0.129778 & 1.0053 & 0.159405 \tabularnewline
27 & -0.178787 & -1.3849 & 0.085609 \tabularnewline
28 & 0.063446 & 0.4914 & 0.312452 \tabularnewline
29 & 0.10165 & 0.7874 & 0.217081 \tabularnewline
30 & -0.18463 & -1.4301 & 0.078933 \tabularnewline
31 & 0.139688 & 1.082 & 0.141786 \tabularnewline
32 & -0.066874 & -0.518 & 0.30318 \tabularnewline
33 & -0.001669 & -0.0129 & 0.494863 \tabularnewline
34 & 0.04531 & 0.351 & 0.363421 \tabularnewline
35 & -0.077296 & -0.5987 & 0.275804 \tabularnewline
36 & 0.010737 & 0.0832 & 0.466997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68839&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]-0.56813[/C][C]-4.4007[/C][C]2.3e-05[/C][/ROW]
[ROW][C]2[/C][C]0.062378[/C][C]0.4832[/C][C]0.315364[/C][/ROW]
[ROW][C]3[/C][C]0.379726[/C][C]2.9413[/C][C]0.002319[/C][/ROW]
[ROW][C]4[/C][C]-0.345198[/C][C]-2.6739[/C][C]0.004823[/C][/ROW]
[ROW][C]5[/C][C]0.123756[/C][C]0.9586[/C][C]0.170802[/C][/ROW]
[ROW][C]6[/C][C]0.192682[/C][C]1.4925[/C][C]0.070402[/C][/ROW]
[ROW][C]7[/C][C]-0.385237[/C][C]-2.984[/C][C]0.002055[/C][/ROW]
[ROW][C]8[/C][C]0.297806[/C][C]2.3068[/C][C]0.012267[/C][/ROW]
[ROW][C]9[/C][C]-0.09298[/C][C]-0.7202[/C][C]0.237092[/C][/ROW]
[ROW][C]10[/C][C]-0.104311[/C][C]-0.808[/C][C]0.211143[/C][/ROW]
[ROW][C]11[/C][C]0.133906[/C][C]1.0372[/C][C]0.151895[/C][/ROW]
[ROW][C]12[/C][C]-0.085221[/C][C]-0.6601[/C][C]0.255853[/C][/ROW]
[ROW][C]13[/C][C]-0.015797[/C][C]-0.1224[/C][C]0.451509[/C][/ROW]
[ROW][C]14[/C][C]0.049047[/C][C]0.3799[/C][C]0.352676[/C][/ROW]
[ROW][C]15[/C][C]0.041122[/C][C]0.3185[/C][C]0.375596[/C][/ROW]
[ROW][C]16[/C][C]-0.173855[/C][C]-1.3467[/C][C]0.091575[/C][/ROW]
[ROW][C]17[/C][C]0.159689[/C][C]1.2369[/C][C]0.110463[/C][/ROW]
[ROW][C]18[/C][C]-0.074326[/C][C]-0.5757[/C][C]0.283478[/C][/ROW]
[ROW][C]19[/C][C]-0.073724[/C][C]-0.5711[/C][C]0.285045[/C][/ROW]
[ROW][C]20[/C][C]0.132778[/C][C]1.0285[/C][C]0.153922[/C][/ROW]
[ROW][C]21[/C][C]-0.038708[/C][C]-0.2998[/C][C]0.382671[/C][/ROW]
[ROW][C]22[/C][C]-0.219262[/C][C]-1.6984[/C][C]0.047307[/C][/ROW]
[ROW][C]23[/C][C]0.404704[/C][C]3.1348[/C][C]0.001331[/C][/ROW]
[ROW][C]24[/C][C]-0.345349[/C][C]-2.6751[/C][C]0.004808[/C][/ROW]
[ROW][C]25[/C][C]0.095725[/C][C]0.7415[/C][C]0.230647[/C][/ROW]
[ROW][C]26[/C][C]0.129778[/C][C]1.0053[/C][C]0.159405[/C][/ROW]
[ROW][C]27[/C][C]-0.178787[/C][C]-1.3849[/C][C]0.085609[/C][/ROW]
[ROW][C]28[/C][C]0.063446[/C][C]0.4914[/C][C]0.312452[/C][/ROW]
[ROW][C]29[/C][C]0.10165[/C][C]0.7874[/C][C]0.217081[/C][/ROW]
[ROW][C]30[/C][C]-0.18463[/C][C]-1.4301[/C][C]0.078933[/C][/ROW]
[ROW][C]31[/C][C]0.139688[/C][C]1.082[/C][C]0.141786[/C][/ROW]
[ROW][C]32[/C][C]-0.066874[/C][C]-0.518[/C][C]0.30318[/C][/ROW]
[ROW][C]33[/C][C]-0.001669[/C][C]-0.0129[/C][C]0.494863[/C][/ROW]
[ROW][C]34[/C][C]0.04531[/C][C]0.351[/C][C]0.363421[/C][/ROW]
[ROW][C]35[/C][C]-0.077296[/C][C]-0.5987[/C][C]0.275804[/C][/ROW]
[ROW][C]36[/C][C]0.010737[/C][C]0.0832[/C][C]0.466997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68839&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68839&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.56813-4.40072.3e-05
20.0623780.48320.315364
30.3797262.94130.002319
4-0.345198-2.67390.004823
50.1237560.95860.170802
60.1926821.49250.070402
7-0.385237-2.9840.002055
80.2978062.30680.012267
9-0.09298-0.72020.237092
10-0.104311-0.8080.211143
110.1339061.03720.151895
12-0.085221-0.66010.255853
13-0.015797-0.12240.451509
140.0490470.37990.352676
150.0411220.31850.375596
16-0.173855-1.34670.091575
170.1596891.23690.110463
18-0.074326-0.57570.283478
19-0.073724-0.57110.285045
200.1327781.02850.153922
21-0.038708-0.29980.382671
22-0.219262-1.69840.047307
230.4047043.13480.001331
24-0.345349-2.67510.004808
250.0957250.74150.230647
260.1297781.00530.159405
27-0.178787-1.38490.085609
280.0634460.49140.312452
290.101650.78740.217081
30-0.18463-1.43010.078933
310.1396881.0820.141786
32-0.066874-0.5180.30318
33-0.001669-0.01290.494863
340.045310.3510.363421
35-0.077296-0.59870.275804
360.0107370.08320.466997






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.56813-4.40072.3e-05
2-0.384499-2.97830.002089
30.3644822.82330.003221
40.2266861.75590.042105
5-0.004806-0.03720.485212
60.0989010.76610.223314
7-0.233858-1.81150.037538
8-0.113908-0.88230.190561
9-0.078885-0.6110.271741
100.0952580.73790.231736
110.0245960.19050.424773
12-0.013823-0.10710.457544
130.0122440.09480.462378
14-0.100163-0.77590.220439
150.1959341.51770.067171
16-0.136256-1.05540.147729
17-0.089859-0.6960.244544
18-0.131793-1.02090.155709
19-0.058917-0.45640.324887
200.0985630.76350.224088
210.2237251.7330.044119
22-0.178835-1.38520.085553
230.0153290.11870.452938
24-0.054227-0.420.337978
250.0050860.03940.484354
26-0.049468-0.38320.351471
270.0906730.70230.242589
28-0.042471-0.3290.371657
29-0.090754-0.7030.242395
300.0901120.6980.243935
310.0331780.2570.39903
32-0.091923-0.7120.239601
33-0.028966-0.22440.411615
34-0.00573-0.04440.482373
35-0.066708-0.51670.303627
36-0.093264-0.72240.236422

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.56813 & -4.4007 & 2.3e-05 \tabularnewline
2 & -0.384499 & -2.9783 & 0.002089 \tabularnewline
3 & 0.364482 & 2.8233 & 0.003221 \tabularnewline
4 & 0.226686 & 1.7559 & 0.042105 \tabularnewline
5 & -0.004806 & -0.0372 & 0.485212 \tabularnewline
6 & 0.098901 & 0.7661 & 0.223314 \tabularnewline
7 & -0.233858 & -1.8115 & 0.037538 \tabularnewline
8 & -0.113908 & -0.8823 & 0.190561 \tabularnewline
9 & -0.078885 & -0.611 & 0.271741 \tabularnewline
10 & 0.095258 & 0.7379 & 0.231736 \tabularnewline
11 & 0.024596 & 0.1905 & 0.424773 \tabularnewline
12 & -0.013823 & -0.1071 & 0.457544 \tabularnewline
13 & 0.012244 & 0.0948 & 0.462378 \tabularnewline
14 & -0.100163 & -0.7759 & 0.220439 \tabularnewline
15 & 0.195934 & 1.5177 & 0.067171 \tabularnewline
16 & -0.136256 & -1.0554 & 0.147729 \tabularnewline
17 & -0.089859 & -0.696 & 0.244544 \tabularnewline
18 & -0.131793 & -1.0209 & 0.155709 \tabularnewline
19 & -0.058917 & -0.4564 & 0.324887 \tabularnewline
20 & 0.098563 & 0.7635 & 0.224088 \tabularnewline
21 & 0.223725 & 1.733 & 0.044119 \tabularnewline
22 & -0.178835 & -1.3852 & 0.085553 \tabularnewline
23 & 0.015329 & 0.1187 & 0.452938 \tabularnewline
24 & -0.054227 & -0.42 & 0.337978 \tabularnewline
25 & 0.005086 & 0.0394 & 0.484354 \tabularnewline
26 & -0.049468 & -0.3832 & 0.351471 \tabularnewline
27 & 0.090673 & 0.7023 & 0.242589 \tabularnewline
28 & -0.042471 & -0.329 & 0.371657 \tabularnewline
29 & -0.090754 & -0.703 & 0.242395 \tabularnewline
30 & 0.090112 & 0.698 & 0.243935 \tabularnewline
31 & 0.033178 & 0.257 & 0.39903 \tabularnewline
32 & -0.091923 & -0.712 & 0.239601 \tabularnewline
33 & -0.028966 & -0.2244 & 0.411615 \tabularnewline
34 & -0.00573 & -0.0444 & 0.482373 \tabularnewline
35 & -0.066708 & -0.5167 & 0.303627 \tabularnewline
36 & -0.093264 & -0.7224 & 0.236422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68839&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]-0.56813[/C][C]-4.4007[/C][C]2.3e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.384499[/C][C]-2.9783[/C][C]0.002089[/C][/ROW]
[ROW][C]3[/C][C]0.364482[/C][C]2.8233[/C][C]0.003221[/C][/ROW]
[ROW][C]4[/C][C]0.226686[/C][C]1.7559[/C][C]0.042105[/C][/ROW]
[ROW][C]5[/C][C]-0.004806[/C][C]-0.0372[/C][C]0.485212[/C][/ROW]
[ROW][C]6[/C][C]0.098901[/C][C]0.7661[/C][C]0.223314[/C][/ROW]
[ROW][C]7[/C][C]-0.233858[/C][C]-1.8115[/C][C]0.037538[/C][/ROW]
[ROW][C]8[/C][C]-0.113908[/C][C]-0.8823[/C][C]0.190561[/C][/ROW]
[ROW][C]9[/C][C]-0.078885[/C][C]-0.611[/C][C]0.271741[/C][/ROW]
[ROW][C]10[/C][C]0.095258[/C][C]0.7379[/C][C]0.231736[/C][/ROW]
[ROW][C]11[/C][C]0.024596[/C][C]0.1905[/C][C]0.424773[/C][/ROW]
[ROW][C]12[/C][C]-0.013823[/C][C]-0.1071[/C][C]0.457544[/C][/ROW]
[ROW][C]13[/C][C]0.012244[/C][C]0.0948[/C][C]0.462378[/C][/ROW]
[ROW][C]14[/C][C]-0.100163[/C][C]-0.7759[/C][C]0.220439[/C][/ROW]
[ROW][C]15[/C][C]0.195934[/C][C]1.5177[/C][C]0.067171[/C][/ROW]
[ROW][C]16[/C][C]-0.136256[/C][C]-1.0554[/C][C]0.147729[/C][/ROW]
[ROW][C]17[/C][C]-0.089859[/C][C]-0.696[/C][C]0.244544[/C][/ROW]
[ROW][C]18[/C][C]-0.131793[/C][C]-1.0209[/C][C]0.155709[/C][/ROW]
[ROW][C]19[/C][C]-0.058917[/C][C]-0.4564[/C][C]0.324887[/C][/ROW]
[ROW][C]20[/C][C]0.098563[/C][C]0.7635[/C][C]0.224088[/C][/ROW]
[ROW][C]21[/C][C]0.223725[/C][C]1.733[/C][C]0.044119[/C][/ROW]
[ROW][C]22[/C][C]-0.178835[/C][C]-1.3852[/C][C]0.085553[/C][/ROW]
[ROW][C]23[/C][C]0.015329[/C][C]0.1187[/C][C]0.452938[/C][/ROW]
[ROW][C]24[/C][C]-0.054227[/C][C]-0.42[/C][C]0.337978[/C][/ROW]
[ROW][C]25[/C][C]0.005086[/C][C]0.0394[/C][C]0.484354[/C][/ROW]
[ROW][C]26[/C][C]-0.049468[/C][C]-0.3832[/C][C]0.351471[/C][/ROW]
[ROW][C]27[/C][C]0.090673[/C][C]0.7023[/C][C]0.242589[/C][/ROW]
[ROW][C]28[/C][C]-0.042471[/C][C]-0.329[/C][C]0.371657[/C][/ROW]
[ROW][C]29[/C][C]-0.090754[/C][C]-0.703[/C][C]0.242395[/C][/ROW]
[ROW][C]30[/C][C]0.090112[/C][C]0.698[/C][C]0.243935[/C][/ROW]
[ROW][C]31[/C][C]0.033178[/C][C]0.257[/C][C]0.39903[/C][/ROW]
[ROW][C]32[/C][C]-0.091923[/C][C]-0.712[/C][C]0.239601[/C][/ROW]
[ROW][C]33[/C][C]-0.028966[/C][C]-0.2244[/C][C]0.411615[/C][/ROW]
[ROW][C]34[/C][C]-0.00573[/C][C]-0.0444[/C][C]0.482373[/C][/ROW]
[ROW][C]35[/C][C]-0.066708[/C][C]-0.5167[/C][C]0.303627[/C][/ROW]
[ROW][C]36[/C][C]-0.093264[/C][C]-0.7224[/C][C]0.236422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68839&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68839&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.56813-4.40072.3e-05
2-0.384499-2.97830.002089
30.3644822.82330.003221
40.2266861.75590.042105
5-0.004806-0.03720.485212
60.0989010.76610.223314
7-0.233858-1.81150.037538
8-0.113908-0.88230.190561
9-0.078885-0.6110.271741
100.0952580.73790.231736
110.0245960.19050.424773
12-0.013823-0.10710.457544
130.0122440.09480.462378
14-0.100163-0.77590.220439
150.1959341.51770.067171
16-0.136256-1.05540.147729
17-0.089859-0.6960.244544
18-0.131793-1.02090.155709
19-0.058917-0.45640.324887
200.0985630.76350.224088
210.2237251.7330.044119
22-0.178835-1.38520.085553
230.0153290.11870.452938
24-0.054227-0.420.337978
250.0050860.03940.484354
26-0.049468-0.38320.351471
270.0906730.70230.242589
28-0.042471-0.3290.371657
29-0.090754-0.7030.242395
300.0901120.6980.243935
310.0331780.2570.39903
32-0.091923-0.7120.239601
33-0.028966-0.22440.411615
34-0.00573-0.04440.482373
35-0.066708-0.51670.303627
36-0.093264-0.72240.236422


Figures (Output of Computation)

Input Parameters & R Code

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')