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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 computationFri, 04 Dec 2009 07:51:28 -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/04/t1259938322g9tggxyx1plingv.htm/, Retrieved Sun, 28 Apr 2024 08:26:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63668, Retrieved Sun, 28 Apr 2024 08:26:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

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]
-    D        [(Partial) Autocorrelation Function] [Shw8: Method 1 AC...] [2009-11-27 10:59:38] [3c8b83428ce260cd44df892bb7619588]
-                 [(Partial) Autocorrelation Function] [Shw8: Method 1 AC...] [2009-12-04 14:51:28] [a5c6be3c0aa55fdb2a703a08e16947ef] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.7461
0.7775
0.7790
0.7744
0.7905
0.7719
0.7811
0.7557
0.7637
0.7595
0.7471
0.7615
0.7487
0.7389
0.7337
0.7510
0.7382
0.7159
0.7542
0.7636
0.7433
0.7658
0.7627
0.7480
0.7692
0.7850
0.7913
0.7720
0.7880
0.8070
0.8268
0.8244
0.8487
0.8572
0.8214
0.8827
0.9216
0.8865
0.8816
0.8884
0.9466
0.9180
0.9337
0.9559
0.9626
0.9434
0.8639
0.7996
0.6680
0.6572
0.6928
0.6438
0.6454
0.6873
0.7265
0.7912
0.8114
0.8281
0.8393

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63668&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]2 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=63668&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63668&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9040656.94430
20.7683855.90210
30.6224754.78136e-06
40.4430613.40320.000601
50.2705762.07830.021019
60.1104050.8480.199923
70.0031510.02420.490387
8-0.087911-0.67530.251075
9-0.132052-1.01430.157289
10-0.131498-1.01010.158298
11-0.142029-1.09090.139866
12-0.163538-1.25620.107005
13-0.17224-1.3230.09547
14-0.165899-1.27430.103778
15-0.196878-1.51220.067905
16-0.23056-1.7710.040866
17-0.223218-1.71460.045837
18-0.229057-1.75940.041845
19-0.232866-1.78870.0394
20-0.214618-1.64850.052282
21-0.204397-1.570.060881
22-0.200462-1.53980.064481
23-0.199974-1.5360.064938
24-0.179596-1.37950.086473
25-0.158154-1.21480.11464
26-0.155515-1.19450.118525
27-0.148478-1.14050.129347
28-0.133886-1.02840.15398
29-0.116633-0.89590.18698
30-0.102983-0.7910.216047
31-0.067433-0.5180.303211
32-0.045475-0.34930.364053
33-0.035704-0.27420.392427
34-0.004041-0.0310.48767
350.0055680.04280.483016
360.0175220.13460.446698

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.904065 & 6.9443 & 0 \tabularnewline
2 & 0.768385 & 5.9021 & 0 \tabularnewline
3 & 0.622475 & 4.7813 & 6e-06 \tabularnewline
4 & 0.443061 & 3.4032 & 0.000601 \tabularnewline
5 & 0.270576 & 2.0783 & 0.021019 \tabularnewline
6 & 0.110405 & 0.848 & 0.199923 \tabularnewline
7 & 0.003151 & 0.0242 & 0.490387 \tabularnewline
8 & -0.087911 & -0.6753 & 0.251075 \tabularnewline
9 & -0.132052 & -1.0143 & 0.157289 \tabularnewline
10 & -0.131498 & -1.0101 & 0.158298 \tabularnewline
11 & -0.142029 & -1.0909 & 0.139866 \tabularnewline
12 & -0.163538 & -1.2562 & 0.107005 \tabularnewline
13 & -0.17224 & -1.323 & 0.09547 \tabularnewline
14 & -0.165899 & -1.2743 & 0.103778 \tabularnewline
15 & -0.196878 & -1.5122 & 0.067905 \tabularnewline
16 & -0.23056 & -1.771 & 0.040866 \tabularnewline
17 & -0.223218 & -1.7146 & 0.045837 \tabularnewline
18 & -0.229057 & -1.7594 & 0.041845 \tabularnewline
19 & -0.232866 & -1.7887 & 0.0394 \tabularnewline
20 & -0.214618 & -1.6485 & 0.052282 \tabularnewline
21 & -0.204397 & -1.57 & 0.060881 \tabularnewline
22 & -0.200462 & -1.5398 & 0.064481 \tabularnewline
23 & -0.199974 & -1.536 & 0.064938 \tabularnewline
24 & -0.179596 & -1.3795 & 0.086473 \tabularnewline
25 & -0.158154 & -1.2148 & 0.11464 \tabularnewline
26 & -0.155515 & -1.1945 & 0.118525 \tabularnewline
27 & -0.148478 & -1.1405 & 0.129347 \tabularnewline
28 & -0.133886 & -1.0284 & 0.15398 \tabularnewline
29 & -0.116633 & -0.8959 & 0.18698 \tabularnewline
30 & -0.102983 & -0.791 & 0.216047 \tabularnewline
31 & -0.067433 & -0.518 & 0.303211 \tabularnewline
32 & -0.045475 & -0.3493 & 0.364053 \tabularnewline
33 & -0.035704 & -0.2742 & 0.392427 \tabularnewline
34 & -0.004041 & -0.031 & 0.48767 \tabularnewline
35 & 0.005568 & 0.0428 & 0.483016 \tabularnewline
36 & 0.017522 & 0.1346 & 0.446698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63668&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]0.904065[/C][C]6.9443[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.768385[/C][C]5.9021[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.622475[/C][C]4.7813[/C][C]6e-06[/C][/ROW]
[ROW][C]4[/C][C]0.443061[/C][C]3.4032[/C][C]0.000601[/C][/ROW]
[ROW][C]5[/C][C]0.270576[/C][C]2.0783[/C][C]0.021019[/C][/ROW]
[ROW][C]6[/C][C]0.110405[/C][C]0.848[/C][C]0.199923[/C][/ROW]
[ROW][C]7[/C][C]0.003151[/C][C]0.0242[/C][C]0.490387[/C][/ROW]
[ROW][C]8[/C][C]-0.087911[/C][C]-0.6753[/C][C]0.251075[/C][/ROW]
[ROW][C]9[/C][C]-0.132052[/C][C]-1.0143[/C][C]0.157289[/C][/ROW]
[ROW][C]10[/C][C]-0.131498[/C][C]-1.0101[/C][C]0.158298[/C][/ROW]
[ROW][C]11[/C][C]-0.142029[/C][C]-1.0909[/C][C]0.139866[/C][/ROW]
[ROW][C]12[/C][C]-0.163538[/C][C]-1.2562[/C][C]0.107005[/C][/ROW]
[ROW][C]13[/C][C]-0.17224[/C][C]-1.323[/C][C]0.09547[/C][/ROW]
[ROW][C]14[/C][C]-0.165899[/C][C]-1.2743[/C][C]0.103778[/C][/ROW]
[ROW][C]15[/C][C]-0.196878[/C][C]-1.5122[/C][C]0.067905[/C][/ROW]
[ROW][C]16[/C][C]-0.23056[/C][C]-1.771[/C][C]0.040866[/C][/ROW]
[ROW][C]17[/C][C]-0.223218[/C][C]-1.7146[/C][C]0.045837[/C][/ROW]
[ROW][C]18[/C][C]-0.229057[/C][C]-1.7594[/C][C]0.041845[/C][/ROW]
[ROW][C]19[/C][C]-0.232866[/C][C]-1.7887[/C][C]0.0394[/C][/ROW]
[ROW][C]20[/C][C]-0.214618[/C][C]-1.6485[/C][C]0.052282[/C][/ROW]
[ROW][C]21[/C][C]-0.204397[/C][C]-1.57[/C][C]0.060881[/C][/ROW]
[ROW][C]22[/C][C]-0.200462[/C][C]-1.5398[/C][C]0.064481[/C][/ROW]
[ROW][C]23[/C][C]-0.199974[/C][C]-1.536[/C][C]0.064938[/C][/ROW]
[ROW][C]24[/C][C]-0.179596[/C][C]-1.3795[/C][C]0.086473[/C][/ROW]
[ROW][C]25[/C][C]-0.158154[/C][C]-1.2148[/C][C]0.11464[/C][/ROW]
[ROW][C]26[/C][C]-0.155515[/C][C]-1.1945[/C][C]0.118525[/C][/ROW]
[ROW][C]27[/C][C]-0.148478[/C][C]-1.1405[/C][C]0.129347[/C][/ROW]
[ROW][C]28[/C][C]-0.133886[/C][C]-1.0284[/C][C]0.15398[/C][/ROW]
[ROW][C]29[/C][C]-0.116633[/C][C]-0.8959[/C][C]0.18698[/C][/ROW]
[ROW][C]30[/C][C]-0.102983[/C][C]-0.791[/C][C]0.216047[/C][/ROW]
[ROW][C]31[/C][C]-0.067433[/C][C]-0.518[/C][C]0.303211[/C][/ROW]
[ROW][C]32[/C][C]-0.045475[/C][C]-0.3493[/C][C]0.364053[/C][/ROW]
[ROW][C]33[/C][C]-0.035704[/C][C]-0.2742[/C][C]0.392427[/C][/ROW]
[ROW][C]34[/C][C]-0.004041[/C][C]-0.031[/C][C]0.48767[/C][/ROW]
[ROW][C]35[/C][C]0.005568[/C][C]0.0428[/C][C]0.483016[/C][/ROW]
[ROW][C]36[/C][C]0.017522[/C][C]0.1346[/C][C]0.446698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63668&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63668&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
10.9040656.94430
20.7683855.90210
30.6224754.78136e-06
40.4430613.40320.000601
50.2705762.07830.021019
60.1104050.8480.199923
70.0031510.02420.490387
8-0.087911-0.67530.251075
9-0.132052-1.01430.157289
10-0.131498-1.01010.158298
11-0.142029-1.09090.139866
12-0.163538-1.25620.107005
13-0.17224-1.3230.09547
14-0.165899-1.27430.103778
15-0.196878-1.51220.067905
16-0.23056-1.7710.040866
17-0.223218-1.71460.045837
18-0.229057-1.75940.041845
19-0.232866-1.78870.0394
20-0.214618-1.64850.052282
21-0.204397-1.570.060881
22-0.200462-1.53980.064481
23-0.199974-1.5360.064938
24-0.179596-1.37950.086473
25-0.158154-1.21480.11464
26-0.155515-1.19450.118525
27-0.148478-1.14050.129347
28-0.133886-1.02840.15398
29-0.116633-0.89590.18698
30-0.102983-0.7910.216047
31-0.067433-0.5180.303211
32-0.045475-0.34930.364053
33-0.035704-0.27420.392427
34-0.004041-0.0310.48767
350.0055680.04280.483016
360.0175220.13460.446698






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9040656.94430
2-0.267962-2.05830.021996
3-0.094872-0.72870.234526
4-0.277137-2.12870.018731
5-0.019837-0.15240.439708
6-0.088315-0.67840.250098
70.2085241.60170.057281
8-0.159033-1.22160.113368
90.2042011.56850.061057
10-0.049828-0.38270.351647
11-0.128847-0.98970.163182
12-0.233936-1.79690.038735
130.1186680.91150.18287
140.0027830.02140.491509
15-0.166553-1.27930.102897
160.0023490.0180.492833
170.1875211.44040.077524
18-0.178059-1.36770.088297
19-0.005784-0.04440.482355
20-0.027506-0.21130.4167
21-0.144312-1.10850.136076
22-0.008426-0.06470.474308
23-0.01782-0.13690.445795
240.0147970.11370.454948
250.0545960.41940.338237
26-0.033884-0.26030.397781
27-0.192007-1.47480.072787
280.0155270.11930.452736
290.0762410.58560.280182
30-0.078332-0.60170.274845
310.0513580.39450.347321
32-0.068178-0.52370.301229
330.025210.19360.423562
34-0.021536-0.16540.434588
35-0.143971-1.10590.136637
360.0866590.66560.254117

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.904065 & 6.9443 & 0 \tabularnewline
2 & -0.267962 & -2.0583 & 0.021996 \tabularnewline
3 & -0.094872 & -0.7287 & 0.234526 \tabularnewline
4 & -0.277137 & -2.1287 & 0.018731 \tabularnewline
5 & -0.019837 & -0.1524 & 0.439708 \tabularnewline
6 & -0.088315 & -0.6784 & 0.250098 \tabularnewline
7 & 0.208524 & 1.6017 & 0.057281 \tabularnewline
8 & -0.159033 & -1.2216 & 0.113368 \tabularnewline
9 & 0.204201 & 1.5685 & 0.061057 \tabularnewline
10 & -0.049828 & -0.3827 & 0.351647 \tabularnewline
11 & -0.128847 & -0.9897 & 0.163182 \tabularnewline
12 & -0.233936 & -1.7969 & 0.038735 \tabularnewline
13 & 0.118668 & 0.9115 & 0.18287 \tabularnewline
14 & 0.002783 & 0.0214 & 0.491509 \tabularnewline
15 & -0.166553 & -1.2793 & 0.102897 \tabularnewline
16 & 0.002349 & 0.018 & 0.492833 \tabularnewline
17 & 0.187521 & 1.4404 & 0.077524 \tabularnewline
18 & -0.178059 & -1.3677 & 0.088297 \tabularnewline
19 & -0.005784 & -0.0444 & 0.482355 \tabularnewline
20 & -0.027506 & -0.2113 & 0.4167 \tabularnewline
21 & -0.144312 & -1.1085 & 0.136076 \tabularnewline
22 & -0.008426 & -0.0647 & 0.474308 \tabularnewline
23 & -0.01782 & -0.1369 & 0.445795 \tabularnewline
24 & 0.014797 & 0.1137 & 0.454948 \tabularnewline
25 & 0.054596 & 0.4194 & 0.338237 \tabularnewline
26 & -0.033884 & -0.2603 & 0.397781 \tabularnewline
27 & -0.192007 & -1.4748 & 0.072787 \tabularnewline
28 & 0.015527 & 0.1193 & 0.452736 \tabularnewline
29 & 0.076241 & 0.5856 & 0.280182 \tabularnewline
30 & -0.078332 & -0.6017 & 0.274845 \tabularnewline
31 & 0.051358 & 0.3945 & 0.347321 \tabularnewline
32 & -0.068178 & -0.5237 & 0.301229 \tabularnewline
33 & 0.02521 & 0.1936 & 0.423562 \tabularnewline
34 & -0.021536 & -0.1654 & 0.434588 \tabularnewline
35 & -0.143971 & -1.1059 & 0.136637 \tabularnewline
36 & 0.086659 & 0.6656 & 0.254117 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63668&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]0.904065[/C][C]6.9443[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.267962[/C][C]-2.0583[/C][C]0.021996[/C][/ROW]
[ROW][C]3[/C][C]-0.094872[/C][C]-0.7287[/C][C]0.234526[/C][/ROW]
[ROW][C]4[/C][C]-0.277137[/C][C]-2.1287[/C][C]0.018731[/C][/ROW]
[ROW][C]5[/C][C]-0.019837[/C][C]-0.1524[/C][C]0.439708[/C][/ROW]
[ROW][C]6[/C][C]-0.088315[/C][C]-0.6784[/C][C]0.250098[/C][/ROW]
[ROW][C]7[/C][C]0.208524[/C][C]1.6017[/C][C]0.057281[/C][/ROW]
[ROW][C]8[/C][C]-0.159033[/C][C]-1.2216[/C][C]0.113368[/C][/ROW]
[ROW][C]9[/C][C]0.204201[/C][C]1.5685[/C][C]0.061057[/C][/ROW]
[ROW][C]10[/C][C]-0.049828[/C][C]-0.3827[/C][C]0.351647[/C][/ROW]
[ROW][C]11[/C][C]-0.128847[/C][C]-0.9897[/C][C]0.163182[/C][/ROW]
[ROW][C]12[/C][C]-0.233936[/C][C]-1.7969[/C][C]0.038735[/C][/ROW]
[ROW][C]13[/C][C]0.118668[/C][C]0.9115[/C][C]0.18287[/C][/ROW]
[ROW][C]14[/C][C]0.002783[/C][C]0.0214[/C][C]0.491509[/C][/ROW]
[ROW][C]15[/C][C]-0.166553[/C][C]-1.2793[/C][C]0.102897[/C][/ROW]
[ROW][C]16[/C][C]0.002349[/C][C]0.018[/C][C]0.492833[/C][/ROW]
[ROW][C]17[/C][C]0.187521[/C][C]1.4404[/C][C]0.077524[/C][/ROW]
[ROW][C]18[/C][C]-0.178059[/C][C]-1.3677[/C][C]0.088297[/C][/ROW]
[ROW][C]19[/C][C]-0.005784[/C][C]-0.0444[/C][C]0.482355[/C][/ROW]
[ROW][C]20[/C][C]-0.027506[/C][C]-0.2113[/C][C]0.4167[/C][/ROW]
[ROW][C]21[/C][C]-0.144312[/C][C]-1.1085[/C][C]0.136076[/C][/ROW]
[ROW][C]22[/C][C]-0.008426[/C][C]-0.0647[/C][C]0.474308[/C][/ROW]
[ROW][C]23[/C][C]-0.01782[/C][C]-0.1369[/C][C]0.445795[/C][/ROW]
[ROW][C]24[/C][C]0.014797[/C][C]0.1137[/C][C]0.454948[/C][/ROW]
[ROW][C]25[/C][C]0.054596[/C][C]0.4194[/C][C]0.338237[/C][/ROW]
[ROW][C]26[/C][C]-0.033884[/C][C]-0.2603[/C][C]0.397781[/C][/ROW]
[ROW][C]27[/C][C]-0.192007[/C][C]-1.4748[/C][C]0.072787[/C][/ROW]
[ROW][C]28[/C][C]0.015527[/C][C]0.1193[/C][C]0.452736[/C][/ROW]
[ROW][C]29[/C][C]0.076241[/C][C]0.5856[/C][C]0.280182[/C][/ROW]
[ROW][C]30[/C][C]-0.078332[/C][C]-0.6017[/C][C]0.274845[/C][/ROW]
[ROW][C]31[/C][C]0.051358[/C][C]0.3945[/C][C]0.347321[/C][/ROW]
[ROW][C]32[/C][C]-0.068178[/C][C]-0.5237[/C][C]0.301229[/C][/ROW]
[ROW][C]33[/C][C]0.02521[/C][C]0.1936[/C][C]0.423562[/C][/ROW]
[ROW][C]34[/C][C]-0.021536[/C][C]-0.1654[/C][C]0.434588[/C][/ROW]
[ROW][C]35[/C][C]-0.143971[/C][C]-1.1059[/C][C]0.136637[/C][/ROW]
[ROW][C]36[/C][C]0.086659[/C][C]0.6656[/C][C]0.254117[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63668&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63668&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
10.9040656.94430
2-0.267962-2.05830.021996
3-0.094872-0.72870.234526
4-0.277137-2.12870.018731
5-0.019837-0.15240.439708
6-0.088315-0.67840.250098
70.2085241.60170.057281
8-0.159033-1.22160.113368
90.2042011.56850.061057
10-0.049828-0.38270.351647
11-0.128847-0.98970.163182
12-0.233936-1.79690.038735
130.1186680.91150.18287
140.0027830.02140.491509
15-0.166553-1.27930.102897
160.0023490.0180.492833
170.1875211.44040.077524
18-0.178059-1.36770.088297
19-0.005784-0.04440.482355
20-0.027506-0.21130.4167
21-0.144312-1.10850.136076
22-0.008426-0.06470.474308
23-0.01782-0.13690.445795
240.0147970.11370.454948
250.0545960.41940.338237
26-0.033884-0.26030.397781
27-0.192007-1.47480.072787
280.0155270.11930.452736
290.0762410.58560.280182
30-0.078332-0.60170.274845
310.0513580.39450.347321
32-0.068178-0.52370.301229
330.025210.19360.423562
34-0.021536-0.16540.434588
35-0.143971-1.10590.136637
360.0866590.66560.254117


Figures (Output of Computation)

Input Parameters & R Code

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