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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, 26 Nov 2009 09:27:14 -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/26/t12592529179mvd7uzonaglstl.htm/, Retrieved Mon, 29 Apr 2024 04:16:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60161, Retrieved Mon, 29 Apr 2024 04:16:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws8ma1.4
Estimated Impact131

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [] [2009-11-24 16:20:41] [1e83ffa964db6f7ea6ccc4e7b5acbbff]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-26 16:27:14] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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=60161&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=60161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60161&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1680991.15240.127487
20.0445350.30530.380738
30.1066690.73130.234117
4-0.003254-0.02230.491148
50.2862911.96270.027807
60.1132420.77630.220716
7-0.189479-1.2990.10014
80.0816260.55960.289206
9-0.051808-0.35520.362024
10-0.01877-0.12870.449079
110.1004770.68880.247156
12-0.284633-1.95130.028495
13-0.114236-0.78320.21873
140.0700850.48050.316558
15-0.041846-0.28690.387731
16-0.03233-0.22160.412776
17-0.205928-1.41180.082302
18-0.244173-1.6740.05039
190.0120730.08280.467194
20-0.117578-0.80610.21213
21-0.09555-0.65510.257811
22-0.147531-1.01140.158497
23-0.143374-0.98290.165338
24-0.082077-0.56270.288161
250.0220820.15140.440159
26-0.019643-0.13470.446726
270.0538950.36950.356712
280.0571730.3920.348431
29-0.020805-0.14260.443594
30-0.018489-0.12680.449837
31-0.045943-0.3150.377089
320.0116730.080.468278
330.0099450.06820.472965
340.0419140.28740.387553
350.0356360.24430.404028
360.0173080.11870.453026

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.168099 & 1.1524 & 0.127487 \tabularnewline
2 & 0.044535 & 0.3053 & 0.380738 \tabularnewline
3 & 0.106669 & 0.7313 & 0.234117 \tabularnewline
4 & -0.003254 & -0.0223 & 0.491148 \tabularnewline
5 & 0.286291 & 1.9627 & 0.027807 \tabularnewline
6 & 0.113242 & 0.7763 & 0.220716 \tabularnewline
7 & -0.189479 & -1.299 & 0.10014 \tabularnewline
8 & 0.081626 & 0.5596 & 0.289206 \tabularnewline
9 & -0.051808 & -0.3552 & 0.362024 \tabularnewline
10 & -0.01877 & -0.1287 & 0.449079 \tabularnewline
11 & 0.100477 & 0.6888 & 0.247156 \tabularnewline
12 & -0.284633 & -1.9513 & 0.028495 \tabularnewline
13 & -0.114236 & -0.7832 & 0.21873 \tabularnewline
14 & 0.070085 & 0.4805 & 0.316558 \tabularnewline
15 & -0.041846 & -0.2869 & 0.387731 \tabularnewline
16 & -0.03233 & -0.2216 & 0.412776 \tabularnewline
17 & -0.205928 & -1.4118 & 0.082302 \tabularnewline
18 & -0.244173 & -1.674 & 0.05039 \tabularnewline
19 & 0.012073 & 0.0828 & 0.467194 \tabularnewline
20 & -0.117578 & -0.8061 & 0.21213 \tabularnewline
21 & -0.09555 & -0.6551 & 0.257811 \tabularnewline
22 & -0.147531 & -1.0114 & 0.158497 \tabularnewline
23 & -0.143374 & -0.9829 & 0.165338 \tabularnewline
24 & -0.082077 & -0.5627 & 0.288161 \tabularnewline
25 & 0.022082 & 0.1514 & 0.440159 \tabularnewline
26 & -0.019643 & -0.1347 & 0.446726 \tabularnewline
27 & 0.053895 & 0.3695 & 0.356712 \tabularnewline
28 & 0.057173 & 0.392 & 0.348431 \tabularnewline
29 & -0.020805 & -0.1426 & 0.443594 \tabularnewline
30 & -0.018489 & -0.1268 & 0.449837 \tabularnewline
31 & -0.045943 & -0.315 & 0.377089 \tabularnewline
32 & 0.011673 & 0.08 & 0.468278 \tabularnewline
33 & 0.009945 & 0.0682 & 0.472965 \tabularnewline
34 & 0.041914 & 0.2874 & 0.387553 \tabularnewline
35 & 0.035636 & 0.2443 & 0.404028 \tabularnewline
36 & 0.017308 & 0.1187 & 0.453026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60161&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]0.168099[/C][C]1.1524[/C][C]0.127487[/C][/ROW]
[ROW][C]2[/C][C]0.044535[/C][C]0.3053[/C][C]0.380738[/C][/ROW]
[ROW][C]3[/C][C]0.106669[/C][C]0.7313[/C][C]0.234117[/C][/ROW]
[ROW][C]4[/C][C]-0.003254[/C][C]-0.0223[/C][C]0.491148[/C][/ROW]
[ROW][C]5[/C][C]0.286291[/C][C]1.9627[/C][C]0.027807[/C][/ROW]
[ROW][C]6[/C][C]0.113242[/C][C]0.7763[/C][C]0.220716[/C][/ROW]
[ROW][C]7[/C][C]-0.189479[/C][C]-1.299[/C][C]0.10014[/C][/ROW]
[ROW][C]8[/C][C]0.081626[/C][C]0.5596[/C][C]0.289206[/C][/ROW]
[ROW][C]9[/C][C]-0.051808[/C][C]-0.3552[/C][C]0.362024[/C][/ROW]
[ROW][C]10[/C][C]-0.01877[/C][C]-0.1287[/C][C]0.449079[/C][/ROW]
[ROW][C]11[/C][C]0.100477[/C][C]0.6888[/C][C]0.247156[/C][/ROW]
[ROW][C]12[/C][C]-0.284633[/C][C]-1.9513[/C][C]0.028495[/C][/ROW]
[ROW][C]13[/C][C]-0.114236[/C][C]-0.7832[/C][C]0.21873[/C][/ROW]
[ROW][C]14[/C][C]0.070085[/C][C]0.4805[/C][C]0.316558[/C][/ROW]
[ROW][C]15[/C][C]-0.041846[/C][C]-0.2869[/C][C]0.387731[/C][/ROW]
[ROW][C]16[/C][C]-0.03233[/C][C]-0.2216[/C][C]0.412776[/C][/ROW]
[ROW][C]17[/C][C]-0.205928[/C][C]-1.4118[/C][C]0.082302[/C][/ROW]
[ROW][C]18[/C][C]-0.244173[/C][C]-1.674[/C][C]0.05039[/C][/ROW]
[ROW][C]19[/C][C]0.012073[/C][C]0.0828[/C][C]0.467194[/C][/ROW]
[ROW][C]20[/C][C]-0.117578[/C][C]-0.8061[/C][C]0.21213[/C][/ROW]
[ROW][C]21[/C][C]-0.09555[/C][C]-0.6551[/C][C]0.257811[/C][/ROW]
[ROW][C]22[/C][C]-0.147531[/C][C]-1.0114[/C][C]0.158497[/C][/ROW]
[ROW][C]23[/C][C]-0.143374[/C][C]-0.9829[/C][C]0.165338[/C][/ROW]
[ROW][C]24[/C][C]-0.082077[/C][C]-0.5627[/C][C]0.288161[/C][/ROW]
[ROW][C]25[/C][C]0.022082[/C][C]0.1514[/C][C]0.440159[/C][/ROW]
[ROW][C]26[/C][C]-0.019643[/C][C]-0.1347[/C][C]0.446726[/C][/ROW]
[ROW][C]27[/C][C]0.053895[/C][C]0.3695[/C][C]0.356712[/C][/ROW]
[ROW][C]28[/C][C]0.057173[/C][C]0.392[/C][C]0.348431[/C][/ROW]
[ROW][C]29[/C][C]-0.020805[/C][C]-0.1426[/C][C]0.443594[/C][/ROW]
[ROW][C]30[/C][C]-0.018489[/C][C]-0.1268[/C][C]0.449837[/C][/ROW]
[ROW][C]31[/C][C]-0.045943[/C][C]-0.315[/C][C]0.377089[/C][/ROW]
[ROW][C]32[/C][C]0.011673[/C][C]0.08[/C][C]0.468278[/C][/ROW]
[ROW][C]33[/C][C]0.009945[/C][C]0.0682[/C][C]0.472965[/C][/ROW]
[ROW][C]34[/C][C]0.041914[/C][C]0.2874[/C][C]0.387553[/C][/ROW]
[ROW][C]35[/C][C]0.035636[/C][C]0.2443[/C][C]0.404028[/C][/ROW]
[ROW][C]36[/C][C]0.017308[/C][C]0.1187[/C][C]0.453026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60161&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
10.1680991.15240.127487
20.0445350.30530.380738
30.1066690.73130.234117
4-0.003254-0.02230.491148
50.2862911.96270.027807
60.1132420.77630.220716
7-0.189479-1.2990.10014
80.0816260.55960.289206
9-0.051808-0.35520.362024
10-0.01877-0.12870.449079
110.1004770.68880.247156
12-0.284633-1.95130.028495
13-0.114236-0.78320.21873
140.0700850.48050.316558
15-0.041846-0.28690.387731
16-0.03233-0.22160.412776
17-0.205928-1.41180.082302
18-0.244173-1.6740.05039
190.0120730.08280.467194
20-0.117578-0.80610.21213
21-0.09555-0.65510.257811
22-0.147531-1.01140.158497
23-0.143374-0.98290.165338
24-0.082077-0.56270.288161
250.0220820.15140.440159
26-0.019643-0.13470.446726
270.0538950.36950.356712
280.0571730.3920.348431
29-0.020805-0.14260.443594
30-0.018489-0.12680.449837
31-0.045943-0.3150.377089
320.0116730.080.468278
330.0099450.06820.472965
340.0419140.28740.387553
350.0356360.24430.404028
360.0173080.11870.453026






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1680991.15240.127487
20.0167510.11480.454532
30.0993260.68090.249623
4-0.038902-0.26670.395435
50.3005232.06030.022466
60.0046210.03170.48743
7-0.234659-1.60870.057186
80.1125790.77180.222047
9-0.076883-0.52710.300307
10-0.049395-0.33860.368197
110.057820.39640.346804
12-0.222092-1.52260.067281
13-0.050862-0.34870.364439
140.1074490.73660.232504
150.0326670.2240.411883
16-0.143321-0.98260.165428
17-0.091812-0.62940.266057
18-0.079919-0.54790.293179
19-0.07307-0.50090.309375
20-0.089089-0.61080.27215
210.0115810.07940.468528
22-0.14036-0.96230.170421
230.0451340.30940.379183
24-0.130663-0.89580.187468
250.0329710.2260.411077
260.0590330.40470.343764
270.1135250.77830.22015
280.0538290.3690.35688
29-0.130313-0.89340.188103
30-0.125983-0.86370.196071
31-0.083888-0.57510.283981
320.0118040.08090.467923
33-0.075528-0.51780.303515
340.0148450.10180.459685
350.0508560.34870.364455
36-0.061004-0.41820.338845

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.168099 & 1.1524 & 0.127487 \tabularnewline
2 & 0.016751 & 0.1148 & 0.454532 \tabularnewline
3 & 0.099326 & 0.6809 & 0.249623 \tabularnewline
4 & -0.038902 & -0.2667 & 0.395435 \tabularnewline
5 & 0.300523 & 2.0603 & 0.022466 \tabularnewline
6 & 0.004621 & 0.0317 & 0.48743 \tabularnewline
7 & -0.234659 & -1.6087 & 0.057186 \tabularnewline
8 & 0.112579 & 0.7718 & 0.222047 \tabularnewline
9 & -0.076883 & -0.5271 & 0.300307 \tabularnewline
10 & -0.049395 & -0.3386 & 0.368197 \tabularnewline
11 & 0.05782 & 0.3964 & 0.346804 \tabularnewline
12 & -0.222092 & -1.5226 & 0.067281 \tabularnewline
13 & -0.050862 & -0.3487 & 0.364439 \tabularnewline
14 & 0.107449 & 0.7366 & 0.232504 \tabularnewline
15 & 0.032667 & 0.224 & 0.411883 \tabularnewline
16 & -0.143321 & -0.9826 & 0.165428 \tabularnewline
17 & -0.091812 & -0.6294 & 0.266057 \tabularnewline
18 & -0.079919 & -0.5479 & 0.293179 \tabularnewline
19 & -0.07307 & -0.5009 & 0.309375 \tabularnewline
20 & -0.089089 & -0.6108 & 0.27215 \tabularnewline
21 & 0.011581 & 0.0794 & 0.468528 \tabularnewline
22 & -0.14036 & -0.9623 & 0.170421 \tabularnewline
23 & 0.045134 & 0.3094 & 0.379183 \tabularnewline
24 & -0.130663 & -0.8958 & 0.187468 \tabularnewline
25 & 0.032971 & 0.226 & 0.411077 \tabularnewline
26 & 0.059033 & 0.4047 & 0.343764 \tabularnewline
27 & 0.113525 & 0.7783 & 0.22015 \tabularnewline
28 & 0.053829 & 0.369 & 0.35688 \tabularnewline
29 & -0.130313 & -0.8934 & 0.188103 \tabularnewline
30 & -0.125983 & -0.8637 & 0.196071 \tabularnewline
31 & -0.083888 & -0.5751 & 0.283981 \tabularnewline
32 & 0.011804 & 0.0809 & 0.467923 \tabularnewline
33 & -0.075528 & -0.5178 & 0.303515 \tabularnewline
34 & 0.014845 & 0.1018 & 0.459685 \tabularnewline
35 & 0.050856 & 0.3487 & 0.364455 \tabularnewline
36 & -0.061004 & -0.4182 & 0.338845 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60161&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]0.168099[/C][C]1.1524[/C][C]0.127487[/C][/ROW]
[ROW][C]2[/C][C]0.016751[/C][C]0.1148[/C][C]0.454532[/C][/ROW]
[ROW][C]3[/C][C]0.099326[/C][C]0.6809[/C][C]0.249623[/C][/ROW]
[ROW][C]4[/C][C]-0.038902[/C][C]-0.2667[/C][C]0.395435[/C][/ROW]
[ROW][C]5[/C][C]0.300523[/C][C]2.0603[/C][C]0.022466[/C][/ROW]
[ROW][C]6[/C][C]0.004621[/C][C]0.0317[/C][C]0.48743[/C][/ROW]
[ROW][C]7[/C][C]-0.234659[/C][C]-1.6087[/C][C]0.057186[/C][/ROW]
[ROW][C]8[/C][C]0.112579[/C][C]0.7718[/C][C]0.222047[/C][/ROW]
[ROW][C]9[/C][C]-0.076883[/C][C]-0.5271[/C][C]0.300307[/C][/ROW]
[ROW][C]10[/C][C]-0.049395[/C][C]-0.3386[/C][C]0.368197[/C][/ROW]
[ROW][C]11[/C][C]0.05782[/C][C]0.3964[/C][C]0.346804[/C][/ROW]
[ROW][C]12[/C][C]-0.222092[/C][C]-1.5226[/C][C]0.067281[/C][/ROW]
[ROW][C]13[/C][C]-0.050862[/C][C]-0.3487[/C][C]0.364439[/C][/ROW]
[ROW][C]14[/C][C]0.107449[/C][C]0.7366[/C][C]0.232504[/C][/ROW]
[ROW][C]15[/C][C]0.032667[/C][C]0.224[/C][C]0.411883[/C][/ROW]
[ROW][C]16[/C][C]-0.143321[/C][C]-0.9826[/C][C]0.165428[/C][/ROW]
[ROW][C]17[/C][C]-0.091812[/C][C]-0.6294[/C][C]0.266057[/C][/ROW]
[ROW][C]18[/C][C]-0.079919[/C][C]-0.5479[/C][C]0.293179[/C][/ROW]
[ROW][C]19[/C][C]-0.07307[/C][C]-0.5009[/C][C]0.309375[/C][/ROW]
[ROW][C]20[/C][C]-0.089089[/C][C]-0.6108[/C][C]0.27215[/C][/ROW]
[ROW][C]21[/C][C]0.011581[/C][C]0.0794[/C][C]0.468528[/C][/ROW]
[ROW][C]22[/C][C]-0.14036[/C][C]-0.9623[/C][C]0.170421[/C][/ROW]
[ROW][C]23[/C][C]0.045134[/C][C]0.3094[/C][C]0.379183[/C][/ROW]
[ROW][C]24[/C][C]-0.130663[/C][C]-0.8958[/C][C]0.187468[/C][/ROW]
[ROW][C]25[/C][C]0.032971[/C][C]0.226[/C][C]0.411077[/C][/ROW]
[ROW][C]26[/C][C]0.059033[/C][C]0.4047[/C][C]0.343764[/C][/ROW]
[ROW][C]27[/C][C]0.113525[/C][C]0.7783[/C][C]0.22015[/C][/ROW]
[ROW][C]28[/C][C]0.053829[/C][C]0.369[/C][C]0.35688[/C][/ROW]
[ROW][C]29[/C][C]-0.130313[/C][C]-0.8934[/C][C]0.188103[/C][/ROW]
[ROW][C]30[/C][C]-0.125983[/C][C]-0.8637[/C][C]0.196071[/C][/ROW]
[ROW][C]31[/C][C]-0.083888[/C][C]-0.5751[/C][C]0.283981[/C][/ROW]
[ROW][C]32[/C][C]0.011804[/C][C]0.0809[/C][C]0.467923[/C][/ROW]
[ROW][C]33[/C][C]-0.075528[/C][C]-0.5178[/C][C]0.303515[/C][/ROW]
[ROW][C]34[/C][C]0.014845[/C][C]0.1018[/C][C]0.459685[/C][/ROW]
[ROW][C]35[/C][C]0.050856[/C][C]0.3487[/C][C]0.364455[/C][/ROW]
[ROW][C]36[/C][C]-0.061004[/C][C]-0.4182[/C][C]0.338845[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60161&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60161&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
10.1680991.15240.127487
20.0167510.11480.454532
30.0993260.68090.249623
4-0.038902-0.26670.395435
50.3005232.06030.022466
60.0046210.03170.48743
7-0.234659-1.60870.057186
80.1125790.77180.222047
9-0.076883-0.52710.300307
10-0.049395-0.33860.368197
110.057820.39640.346804
12-0.222092-1.52260.067281
13-0.050862-0.34870.364439
140.1074490.73660.232504
150.0326670.2240.411883
16-0.143321-0.98260.165428
17-0.091812-0.62940.266057
18-0.079919-0.54790.293179
19-0.07307-0.50090.309375
20-0.089089-0.61080.27215
210.0115810.07940.468528
22-0.14036-0.96230.170421
230.0451340.30940.379183
24-0.130663-0.89580.187468
250.0329710.2260.411077
260.0590330.40470.343764
270.1135250.77830.22015
280.0538290.3690.35688
29-0.130313-0.89340.188103
30-0.125983-0.86370.196071
31-0.083888-0.57510.283981
320.0118040.08090.467923
33-0.075528-0.51780.303515
340.0148450.10180.459685
350.0508560.34870.364455
36-0.061004-0.41820.338845


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')