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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, 27 Nov 2009 09:03:39 -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/t12593379926ll6yd659vf6gno.htm/, Retrieved Mon, 29 Apr 2024 01:18:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60938, Retrieved Mon, 29 Apr 2024 01:18:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWSACFd1MLDG
Estimated Impact160

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] [Workshop 8: autoc...] [2009-11-27 15:53:36] [7c2a5b25a196bd646844b8f5223c9b3e]
-   P             [(Partial) Autocorrelation Function] [Workshop 8: autoc...] [2009-11-27 16:03:39] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
-   P               [(Partial) Autocorrelation Function] [Workshop 8: autoc...] [2009-11-27 16:14:31] [7c2a5b25a196bd646844b8f5223c9b3e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710
295881
293299

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=60938&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=60938&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60938&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
10.1590281.31140.09707
2-0.162336-1.33870.09257
3-0.186933-1.54150.06392
4-0.168894-1.39270.084119
50.1134290.93540.176455
60.214421.76820.040761
70.117940.97260.167109
8-0.171049-1.41050.081475
9-0.195601-1.6130.055691
10-0.194736-1.60580.056472
110.1536071.26670.104796
120.6948545.72990
130.0192290.15860.43724
14-0.171154-1.41140.081347
15-0.207955-1.71480.045464
16-0.191424-1.57850.059543
170.070590.58210.281211
180.118350.97590.166276
190.0434120.3580.360733
20-0.213386-1.75960.041484
21-0.202509-1.66990.049765
22-0.161807-1.33430.09328
230.10480.86420.195257
240.4850333.99977.9e-05
25-0.047509-0.39180.348226
26-0.172095-1.41910.080215
27-0.216662-1.78660.039227
28-0.14485-1.19450.118223
290.0487730.40220.344401
300.1152860.95070.172568
310.0163550.13490.446557
32-0.198176-1.63420.05342
33-0.157305-1.29720.099478
34-0.110344-0.90990.18304
350.087090.71820.237559
360.3529542.91050.002437

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.159028 & 1.3114 & 0.09707 \tabularnewline
2 & -0.162336 & -1.3387 & 0.09257 \tabularnewline
3 & -0.186933 & -1.5415 & 0.06392 \tabularnewline
4 & -0.168894 & -1.3927 & 0.084119 \tabularnewline
5 & 0.113429 & 0.9354 & 0.176455 \tabularnewline
6 & 0.21442 & 1.7682 & 0.040761 \tabularnewline
7 & 0.11794 & 0.9726 & 0.167109 \tabularnewline
8 & -0.171049 & -1.4105 & 0.081475 \tabularnewline
9 & -0.195601 & -1.613 & 0.055691 \tabularnewline
10 & -0.194736 & -1.6058 & 0.056472 \tabularnewline
11 & 0.153607 & 1.2667 & 0.104796 \tabularnewline
12 & 0.694854 & 5.7299 & 0 \tabularnewline
13 & 0.019229 & 0.1586 & 0.43724 \tabularnewline
14 & -0.171154 & -1.4114 & 0.081347 \tabularnewline
15 & -0.207955 & -1.7148 & 0.045464 \tabularnewline
16 & -0.191424 & -1.5785 & 0.059543 \tabularnewline
17 & 0.07059 & 0.5821 & 0.281211 \tabularnewline
18 & 0.11835 & 0.9759 & 0.166276 \tabularnewline
19 & 0.043412 & 0.358 & 0.360733 \tabularnewline
20 & -0.213386 & -1.7596 & 0.041484 \tabularnewline
21 & -0.202509 & -1.6699 & 0.049765 \tabularnewline
22 & -0.161807 & -1.3343 & 0.09328 \tabularnewline
23 & 0.1048 & 0.8642 & 0.195257 \tabularnewline
24 & 0.485033 & 3.9997 & 7.9e-05 \tabularnewline
25 & -0.047509 & -0.3918 & 0.348226 \tabularnewline
26 & -0.172095 & -1.4191 & 0.080215 \tabularnewline
27 & -0.216662 & -1.7866 & 0.039227 \tabularnewline
28 & -0.14485 & -1.1945 & 0.118223 \tabularnewline
29 & 0.048773 & 0.4022 & 0.344401 \tabularnewline
30 & 0.115286 & 0.9507 & 0.172568 \tabularnewline
31 & 0.016355 & 0.1349 & 0.446557 \tabularnewline
32 & -0.198176 & -1.6342 & 0.05342 \tabularnewline
33 & -0.157305 & -1.2972 & 0.099478 \tabularnewline
34 & -0.110344 & -0.9099 & 0.18304 \tabularnewline
35 & 0.08709 & 0.7182 & 0.237559 \tabularnewline
36 & 0.352954 & 2.9105 & 0.002437 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60938&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]0.159028[/C][C]1.3114[/C][C]0.09707[/C][/ROW]
[ROW][C]2[/C][C]-0.162336[/C][C]-1.3387[/C][C]0.09257[/C][/ROW]
[ROW][C]3[/C][C]-0.186933[/C][C]-1.5415[/C][C]0.06392[/C][/ROW]
[ROW][C]4[/C][C]-0.168894[/C][C]-1.3927[/C][C]0.084119[/C][/ROW]
[ROW][C]5[/C][C]0.113429[/C][C]0.9354[/C][C]0.176455[/C][/ROW]
[ROW][C]6[/C][C]0.21442[/C][C]1.7682[/C][C]0.040761[/C][/ROW]
[ROW][C]7[/C][C]0.11794[/C][C]0.9726[/C][C]0.167109[/C][/ROW]
[ROW][C]8[/C][C]-0.171049[/C][C]-1.4105[/C][C]0.081475[/C][/ROW]
[ROW][C]9[/C][C]-0.195601[/C][C]-1.613[/C][C]0.055691[/C][/ROW]
[ROW][C]10[/C][C]-0.194736[/C][C]-1.6058[/C][C]0.056472[/C][/ROW]
[ROW][C]11[/C][C]0.153607[/C][C]1.2667[/C][C]0.104796[/C][/ROW]
[ROW][C]12[/C][C]0.694854[/C][C]5.7299[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.019229[/C][C]0.1586[/C][C]0.43724[/C][/ROW]
[ROW][C]14[/C][C]-0.171154[/C][C]-1.4114[/C][C]0.081347[/C][/ROW]
[ROW][C]15[/C][C]-0.207955[/C][C]-1.7148[/C][C]0.045464[/C][/ROW]
[ROW][C]16[/C][C]-0.191424[/C][C]-1.5785[/C][C]0.059543[/C][/ROW]
[ROW][C]17[/C][C]0.07059[/C][C]0.5821[/C][C]0.281211[/C][/ROW]
[ROW][C]18[/C][C]0.11835[/C][C]0.9759[/C][C]0.166276[/C][/ROW]
[ROW][C]19[/C][C]0.043412[/C][C]0.358[/C][C]0.360733[/C][/ROW]
[ROW][C]20[/C][C]-0.213386[/C][C]-1.7596[/C][C]0.041484[/C][/ROW]
[ROW][C]21[/C][C]-0.202509[/C][C]-1.6699[/C][C]0.049765[/C][/ROW]
[ROW][C]22[/C][C]-0.161807[/C][C]-1.3343[/C][C]0.09328[/C][/ROW]
[ROW][C]23[/C][C]0.1048[/C][C]0.8642[/C][C]0.195257[/C][/ROW]
[ROW][C]24[/C][C]0.485033[/C][C]3.9997[/C][C]7.9e-05[/C][/ROW]
[ROW][C]25[/C][C]-0.047509[/C][C]-0.3918[/C][C]0.348226[/C][/ROW]
[ROW][C]26[/C][C]-0.172095[/C][C]-1.4191[/C][C]0.080215[/C][/ROW]
[ROW][C]27[/C][C]-0.216662[/C][C]-1.7866[/C][C]0.039227[/C][/ROW]
[ROW][C]28[/C][C]-0.14485[/C][C]-1.1945[/C][C]0.118223[/C][/ROW]
[ROW][C]29[/C][C]0.048773[/C][C]0.4022[/C][C]0.344401[/C][/ROW]
[ROW][C]30[/C][C]0.115286[/C][C]0.9507[/C][C]0.172568[/C][/ROW]
[ROW][C]31[/C][C]0.016355[/C][C]0.1349[/C][C]0.446557[/C][/ROW]
[ROW][C]32[/C][C]-0.198176[/C][C]-1.6342[/C][C]0.05342[/C][/ROW]
[ROW][C]33[/C][C]-0.157305[/C][C]-1.2972[/C][C]0.099478[/C][/ROW]
[ROW][C]34[/C][C]-0.110344[/C][C]-0.9099[/C][C]0.18304[/C][/ROW]
[ROW][C]35[/C][C]0.08709[/C][C]0.7182[/C][C]0.237559[/C][/ROW]
[ROW][C]36[/C][C]0.352954[/C][C]2.9105[/C][C]0.002437[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60938&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60938&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
10.1590281.31140.09707
2-0.162336-1.33870.09257
3-0.186933-1.54150.06392
4-0.168894-1.39270.084119
50.1134290.93540.176455
60.214421.76820.040761
70.117940.97260.167109
8-0.171049-1.41050.081475
9-0.195601-1.6130.055691
10-0.194736-1.60580.056472
110.1536071.26670.104796
120.6948545.72990
130.0192290.15860.43724
14-0.171154-1.41140.081347
15-0.207955-1.71480.045464
16-0.191424-1.57850.059543
170.070590.58210.281211
180.118350.97590.166276
190.0434120.3580.360733
20-0.213386-1.75960.041484
21-0.202509-1.66990.049765
22-0.161807-1.33430.09328
230.10480.86420.195257
240.4850333.99977.9e-05
25-0.047509-0.39180.348226
26-0.172095-1.41910.080215
27-0.216662-1.78660.039227
28-0.14485-1.19450.118223
290.0487730.40220.344401
300.1152860.95070.172568
310.0163550.13490.446557
32-0.198176-1.63420.05342
33-0.157305-1.29720.099478
34-0.110344-0.90990.18304
350.087090.71820.237559
360.3529542.91050.002437






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1590281.31140.09707
2-0.192494-1.58740.058536
3-0.133748-1.10290.136976
4-0.156344-1.28920.100841
50.1209450.99730.161068
60.1155160.95260.172091
70.0702120.5790.282257
8-0.163436-1.34770.09111
9-0.058715-0.48420.314907
10-0.176884-1.45860.074636
110.1619361.33540.093106
120.6180415.09651e-06
13-0.257949-2.12710.018521
14-0.017572-0.14490.442609
15-0.051231-0.42250.33701
16-0.06779-0.5590.288996
17-0.063912-0.5270.299944
18-0.16918-1.39510.083764
19-0.071563-0.59010.278533
20-0.091015-0.75050.227763
21-0.014667-0.12090.452045
220.0361830.29840.383164
23-0.139559-1.15080.126916
240.0415210.34240.366557
25-0.022719-0.18730.425975
26-0.06119-0.50460.307741
27-0.054742-0.45140.326563
280.0100440.08280.467118
29-0.078183-0.64470.260641
300.0656890.54170.294903
31-0.081222-0.66980.252635
320.0063230.05210.479284
33-0.036783-0.30330.381287
34-0.019824-0.16350.435317
35-0.061004-0.5030.308278
36-0.072707-0.59960.275396

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.159028 & 1.3114 & 0.09707 \tabularnewline
2 & -0.192494 & -1.5874 & 0.058536 \tabularnewline
3 & -0.133748 & -1.1029 & 0.136976 \tabularnewline
4 & -0.156344 & -1.2892 & 0.100841 \tabularnewline
5 & 0.120945 & 0.9973 & 0.161068 \tabularnewline
6 & 0.115516 & 0.9526 & 0.172091 \tabularnewline
7 & 0.070212 & 0.579 & 0.282257 \tabularnewline
8 & -0.163436 & -1.3477 & 0.09111 \tabularnewline
9 & -0.058715 & -0.4842 & 0.314907 \tabularnewline
10 & -0.176884 & -1.4586 & 0.074636 \tabularnewline
11 & 0.161936 & 1.3354 & 0.093106 \tabularnewline
12 & 0.618041 & 5.0965 & 1e-06 \tabularnewline
13 & -0.257949 & -2.1271 & 0.018521 \tabularnewline
14 & -0.017572 & -0.1449 & 0.442609 \tabularnewline
15 & -0.051231 & -0.4225 & 0.33701 \tabularnewline
16 & -0.06779 & -0.559 & 0.288996 \tabularnewline
17 & -0.063912 & -0.527 & 0.299944 \tabularnewline
18 & -0.16918 & -1.3951 & 0.083764 \tabularnewline
19 & -0.071563 & -0.5901 & 0.278533 \tabularnewline
20 & -0.091015 & -0.7505 & 0.227763 \tabularnewline
21 & -0.014667 & -0.1209 & 0.452045 \tabularnewline
22 & 0.036183 & 0.2984 & 0.383164 \tabularnewline
23 & -0.139559 & -1.1508 & 0.126916 \tabularnewline
24 & 0.041521 & 0.3424 & 0.366557 \tabularnewline
25 & -0.022719 & -0.1873 & 0.425975 \tabularnewline
26 & -0.06119 & -0.5046 & 0.307741 \tabularnewline
27 & -0.054742 & -0.4514 & 0.326563 \tabularnewline
28 & 0.010044 & 0.0828 & 0.467118 \tabularnewline
29 & -0.078183 & -0.6447 & 0.260641 \tabularnewline
30 & 0.065689 & 0.5417 & 0.294903 \tabularnewline
31 & -0.081222 & -0.6698 & 0.252635 \tabularnewline
32 & 0.006323 & 0.0521 & 0.479284 \tabularnewline
33 & -0.036783 & -0.3033 & 0.381287 \tabularnewline
34 & -0.019824 & -0.1635 & 0.435317 \tabularnewline
35 & -0.061004 & -0.503 & 0.308278 \tabularnewline
36 & -0.072707 & -0.5996 & 0.275396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60938&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]0.159028[/C][C]1.3114[/C][C]0.09707[/C][/ROW]
[ROW][C]2[/C][C]-0.192494[/C][C]-1.5874[/C][C]0.058536[/C][/ROW]
[ROW][C]3[/C][C]-0.133748[/C][C]-1.1029[/C][C]0.136976[/C][/ROW]
[ROW][C]4[/C][C]-0.156344[/C][C]-1.2892[/C][C]0.100841[/C][/ROW]
[ROW][C]5[/C][C]0.120945[/C][C]0.9973[/C][C]0.161068[/C][/ROW]
[ROW][C]6[/C][C]0.115516[/C][C]0.9526[/C][C]0.172091[/C][/ROW]
[ROW][C]7[/C][C]0.070212[/C][C]0.579[/C][C]0.282257[/C][/ROW]
[ROW][C]8[/C][C]-0.163436[/C][C]-1.3477[/C][C]0.09111[/C][/ROW]
[ROW][C]9[/C][C]-0.058715[/C][C]-0.4842[/C][C]0.314907[/C][/ROW]
[ROW][C]10[/C][C]-0.176884[/C][C]-1.4586[/C][C]0.074636[/C][/ROW]
[ROW][C]11[/C][C]0.161936[/C][C]1.3354[/C][C]0.093106[/C][/ROW]
[ROW][C]12[/C][C]0.618041[/C][C]5.0965[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.257949[/C][C]-2.1271[/C][C]0.018521[/C][/ROW]
[ROW][C]14[/C][C]-0.017572[/C][C]-0.1449[/C][C]0.442609[/C][/ROW]
[ROW][C]15[/C][C]-0.051231[/C][C]-0.4225[/C][C]0.33701[/C][/ROW]
[ROW][C]16[/C][C]-0.06779[/C][C]-0.559[/C][C]0.288996[/C][/ROW]
[ROW][C]17[/C][C]-0.063912[/C][C]-0.527[/C][C]0.299944[/C][/ROW]
[ROW][C]18[/C][C]-0.16918[/C][C]-1.3951[/C][C]0.083764[/C][/ROW]
[ROW][C]19[/C][C]-0.071563[/C][C]-0.5901[/C][C]0.278533[/C][/ROW]
[ROW][C]20[/C][C]-0.091015[/C][C]-0.7505[/C][C]0.227763[/C][/ROW]
[ROW][C]21[/C][C]-0.014667[/C][C]-0.1209[/C][C]0.452045[/C][/ROW]
[ROW][C]22[/C][C]0.036183[/C][C]0.2984[/C][C]0.383164[/C][/ROW]
[ROW][C]23[/C][C]-0.139559[/C][C]-1.1508[/C][C]0.126916[/C][/ROW]
[ROW][C]24[/C][C]0.041521[/C][C]0.3424[/C][C]0.366557[/C][/ROW]
[ROW][C]25[/C][C]-0.022719[/C][C]-0.1873[/C][C]0.425975[/C][/ROW]
[ROW][C]26[/C][C]-0.06119[/C][C]-0.5046[/C][C]0.307741[/C][/ROW]
[ROW][C]27[/C][C]-0.054742[/C][C]-0.4514[/C][C]0.326563[/C][/ROW]
[ROW][C]28[/C][C]0.010044[/C][C]0.0828[/C][C]0.467118[/C][/ROW]
[ROW][C]29[/C][C]-0.078183[/C][C]-0.6447[/C][C]0.260641[/C][/ROW]
[ROW][C]30[/C][C]0.065689[/C][C]0.5417[/C][C]0.294903[/C][/ROW]
[ROW][C]31[/C][C]-0.081222[/C][C]-0.6698[/C][C]0.252635[/C][/ROW]
[ROW][C]32[/C][C]0.006323[/C][C]0.0521[/C][C]0.479284[/C][/ROW]
[ROW][C]33[/C][C]-0.036783[/C][C]-0.3033[/C][C]0.381287[/C][/ROW]
[ROW][C]34[/C][C]-0.019824[/C][C]-0.1635[/C][C]0.435317[/C][/ROW]
[ROW][C]35[/C][C]-0.061004[/C][C]-0.503[/C][C]0.308278[/C][/ROW]
[ROW][C]36[/C][C]-0.072707[/C][C]-0.5996[/C][C]0.275396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60938&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60938&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
10.1590281.31140.09707
2-0.192494-1.58740.058536
3-0.133748-1.10290.136976
4-0.156344-1.28920.100841
50.1209450.99730.161068
60.1155160.95260.172091
70.0702120.5790.282257
8-0.163436-1.34770.09111
9-0.058715-0.48420.314907
10-0.176884-1.45860.074636
110.1619361.33540.093106
120.6180415.09651e-06
13-0.257949-2.12710.018521
14-0.017572-0.14490.442609
15-0.051231-0.42250.33701
16-0.06779-0.5590.288996
17-0.063912-0.5270.299944
18-0.16918-1.39510.083764
19-0.071563-0.59010.278533
20-0.091015-0.75050.227763
21-0.014667-0.12090.452045
220.0361830.29840.383164
23-0.139559-1.15080.126916
240.0415210.34240.366557
25-0.022719-0.18730.425975
26-0.06119-0.50460.307741
27-0.054742-0.45140.326563
280.0100440.08280.467118
29-0.078183-0.64470.260641
300.0656890.54170.294903
31-0.081222-0.66980.252635
320.0063230.05210.479284
33-0.036783-0.30330.381287
34-0.019824-0.16350.435317
35-0.061004-0.5030.308278
36-0.072707-0.59960.275396


Figures (Output of Computation)

Input Parameters & R Code

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