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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, 03 Dec 2009 08:02:43 -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/03/t125985262221s9otmg8gzokea.htm/, Retrieved Sat, 20 Apr 2024 00:46:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62820, Retrieved Sat, 20 Apr 2024 00:46:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

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]
- R PD        [(Partial) Autocorrelation Function] [] [2009-12-02 16:12:55] [74be16979710d4c4e7c6647856088456]
-   P             [(Partial) Autocorrelation Function] [eerst gewoon diff...] [2009-12-03 15:02:43] [ea241b681aafed79da4b5b99fad98471] [Current]
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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

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=62820&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=62820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62820&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
10.1482731.20460.116335
2-0.151545-1.23120.111317
3-0.180214-1.46410.073962
4-0.174711-1.41940.08025
50.1114190.90520.184334
60.2158891.75390.042046
70.1156110.93920.175519
8-0.171968-1.39710.083535
9-0.190495-1.54760.063252
10-0.193444-1.57150.060419
110.153811.24960.107937
120.6963595.65720
130.0057810.0470.481342
14-0.157959-1.28330.101943
15-0.2003-1.62720.054225
16-0.200185-1.62630.054325
170.0760890.61820.269302
180.1155830.9390.175577
190.040220.32680.372444
20-0.21561-1.75160.042242
21-0.195988-1.59220.058058
22-0.16482-1.3390.092581
230.1065610.86570.194893
240.480923.9070.000111
25-0.061177-0.4970.310419
26-0.149622-1.21550.114247
27-0.220157-1.78860.039137
28-0.149283-1.21280.114769
290.0535540.43510.332464
300.112670.91530.181674
310.010960.0890.464661
32-0.194141-1.57720.059764
33-0.155003-1.25920.106188
34-0.107802-0.87580.19216
350.0767670.62370.267502
360.3547872.88230.002661

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.148273 & 1.2046 & 0.116335 \tabularnewline
2 & -0.151545 & -1.2312 & 0.111317 \tabularnewline
3 & -0.180214 & -1.4641 & 0.073962 \tabularnewline
4 & -0.174711 & -1.4194 & 0.08025 \tabularnewline
5 & 0.111419 & 0.9052 & 0.184334 \tabularnewline
6 & 0.215889 & 1.7539 & 0.042046 \tabularnewline
7 & 0.115611 & 0.9392 & 0.175519 \tabularnewline
8 & -0.171968 & -1.3971 & 0.083535 \tabularnewline
9 & -0.190495 & -1.5476 & 0.063252 \tabularnewline
10 & -0.193444 & -1.5715 & 0.060419 \tabularnewline
11 & 0.15381 & 1.2496 & 0.107937 \tabularnewline
12 & 0.696359 & 5.6572 & 0 \tabularnewline
13 & 0.005781 & 0.047 & 0.481342 \tabularnewline
14 & -0.157959 & -1.2833 & 0.101943 \tabularnewline
15 & -0.2003 & -1.6272 & 0.054225 \tabularnewline
16 & -0.200185 & -1.6263 & 0.054325 \tabularnewline
17 & 0.076089 & 0.6182 & 0.269302 \tabularnewline
18 & 0.115583 & 0.939 & 0.175577 \tabularnewline
19 & 0.04022 & 0.3268 & 0.372444 \tabularnewline
20 & -0.21561 & -1.7516 & 0.042242 \tabularnewline
21 & -0.195988 & -1.5922 & 0.058058 \tabularnewline
22 & -0.16482 & -1.339 & 0.092581 \tabularnewline
23 & 0.106561 & 0.8657 & 0.194893 \tabularnewline
24 & 0.48092 & 3.907 & 0.000111 \tabularnewline
25 & -0.061177 & -0.497 & 0.310419 \tabularnewline
26 & -0.149622 & -1.2155 & 0.114247 \tabularnewline
27 & -0.220157 & -1.7886 & 0.039137 \tabularnewline
28 & -0.149283 & -1.2128 & 0.114769 \tabularnewline
29 & 0.053554 & 0.4351 & 0.332464 \tabularnewline
30 & 0.11267 & 0.9153 & 0.181674 \tabularnewline
31 & 0.01096 & 0.089 & 0.464661 \tabularnewline
32 & -0.194141 & -1.5772 & 0.059764 \tabularnewline
33 & -0.155003 & -1.2592 & 0.106188 \tabularnewline
34 & -0.107802 & -0.8758 & 0.19216 \tabularnewline
35 & 0.076767 & 0.6237 & 0.267502 \tabularnewline
36 & 0.354787 & 2.8823 & 0.002661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62820&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]0.148273[/C][C]1.2046[/C][C]0.116335[/C][/ROW]
[ROW][C]2[/C][C]-0.151545[/C][C]-1.2312[/C][C]0.111317[/C][/ROW]
[ROW][C]3[/C][C]-0.180214[/C][C]-1.4641[/C][C]0.073962[/C][/ROW]
[ROW][C]4[/C][C]-0.174711[/C][C]-1.4194[/C][C]0.08025[/C][/ROW]
[ROW][C]5[/C][C]0.111419[/C][C]0.9052[/C][C]0.184334[/C][/ROW]
[ROW][C]6[/C][C]0.215889[/C][C]1.7539[/C][C]0.042046[/C][/ROW]
[ROW][C]7[/C][C]0.115611[/C][C]0.9392[/C][C]0.175519[/C][/ROW]
[ROW][C]8[/C][C]-0.171968[/C][C]-1.3971[/C][C]0.083535[/C][/ROW]
[ROW][C]9[/C][C]-0.190495[/C][C]-1.5476[/C][C]0.063252[/C][/ROW]
[ROW][C]10[/C][C]-0.193444[/C][C]-1.5715[/C][C]0.060419[/C][/ROW]
[ROW][C]11[/C][C]0.15381[/C][C]1.2496[/C][C]0.107937[/C][/ROW]
[ROW][C]12[/C][C]0.696359[/C][C]5.6572[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.005781[/C][C]0.047[/C][C]0.481342[/C][/ROW]
[ROW][C]14[/C][C]-0.157959[/C][C]-1.2833[/C][C]0.101943[/C][/ROW]
[ROW][C]15[/C][C]-0.2003[/C][C]-1.6272[/C][C]0.054225[/C][/ROW]
[ROW][C]16[/C][C]-0.200185[/C][C]-1.6263[/C][C]0.054325[/C][/ROW]
[ROW][C]17[/C][C]0.076089[/C][C]0.6182[/C][C]0.269302[/C][/ROW]
[ROW][C]18[/C][C]0.115583[/C][C]0.939[/C][C]0.175577[/C][/ROW]
[ROW][C]19[/C][C]0.04022[/C][C]0.3268[/C][C]0.372444[/C][/ROW]
[ROW][C]20[/C][C]-0.21561[/C][C]-1.7516[/C][C]0.042242[/C][/ROW]
[ROW][C]21[/C][C]-0.195988[/C][C]-1.5922[/C][C]0.058058[/C][/ROW]
[ROW][C]22[/C][C]-0.16482[/C][C]-1.339[/C][C]0.092581[/C][/ROW]
[ROW][C]23[/C][C]0.106561[/C][C]0.8657[/C][C]0.194893[/C][/ROW]
[ROW][C]24[/C][C]0.48092[/C][C]3.907[/C][C]0.000111[/C][/ROW]
[ROW][C]25[/C][C]-0.061177[/C][C]-0.497[/C][C]0.310419[/C][/ROW]
[ROW][C]26[/C][C]-0.149622[/C][C]-1.2155[/C][C]0.114247[/C][/ROW]
[ROW][C]27[/C][C]-0.220157[/C][C]-1.7886[/C][C]0.039137[/C][/ROW]
[ROW][C]28[/C][C]-0.149283[/C][C]-1.2128[/C][C]0.114769[/C][/ROW]
[ROW][C]29[/C][C]0.053554[/C][C]0.4351[/C][C]0.332464[/C][/ROW]
[ROW][C]30[/C][C]0.11267[/C][C]0.9153[/C][C]0.181674[/C][/ROW]
[ROW][C]31[/C][C]0.01096[/C][C]0.089[/C][C]0.464661[/C][/ROW]
[ROW][C]32[/C][C]-0.194141[/C][C]-1.5772[/C][C]0.059764[/C][/ROW]
[ROW][C]33[/C][C]-0.155003[/C][C]-1.2592[/C][C]0.106188[/C][/ROW]
[ROW][C]34[/C][C]-0.107802[/C][C]-0.8758[/C][C]0.19216[/C][/ROW]
[ROW][C]35[/C][C]0.076767[/C][C]0.6237[/C][C]0.267502[/C][/ROW]
[ROW][C]36[/C][C]0.354787[/C][C]2.8823[/C][C]0.002661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62820&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
10.1482731.20460.116335
2-0.151545-1.23120.111317
3-0.180214-1.46410.073962
4-0.174711-1.41940.08025
50.1114190.90520.184334
60.2158891.75390.042046
70.1156110.93920.175519
8-0.171968-1.39710.083535
9-0.190495-1.54760.063252
10-0.193444-1.57150.060419
110.153811.24960.107937
120.6963595.65720
130.0057810.0470.481342
14-0.157959-1.28330.101943
15-0.2003-1.62720.054225
16-0.200185-1.62630.054325
170.0760890.61820.269302
180.1155830.9390.175577
190.040220.32680.372444
20-0.21561-1.75160.042242
21-0.195988-1.59220.058058
22-0.16482-1.3390.092581
230.1065610.86570.194893
240.480923.9070.000111
25-0.061177-0.4970.310419
26-0.149622-1.21550.114247
27-0.220157-1.78860.039137
28-0.149283-1.21280.114769
290.0535540.43510.332464
300.112670.91530.181674
310.010960.0890.464661
32-0.194141-1.57720.059764
33-0.155003-1.25920.106188
34-0.107802-0.87580.19216
350.0767670.62370.267502
360.3547872.88230.002661






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1482731.20460.116335
2-0.17743-1.44150.077093
3-0.13455-1.09310.139164
4-0.162277-1.31830.095973
50.1204380.97840.165713
60.1228650.99820.160924
70.0661180.53710.296488
8-0.166234-1.35050.090736
9-0.058843-0.4780.317099
10-0.170902-1.38840.08484
110.1589821.29160.100505
120.6240125.06952e-06
13-0.261332-2.12310.018751
14-0.026084-0.21190.416415
15-0.039474-0.32070.374729
16-0.071631-0.58190.281298
17-0.05193-0.42190.337243
18-0.183949-1.49440.069917
19-0.071009-0.57690.282991
20-0.09635-0.78280.218287
21-0.001916-0.01560.493814
220.0323580.26290.396731
23-0.152827-1.24160.109395
240.0334750.2720.393254
25-0.011187-0.09090.463932
26-0.044649-0.36270.358983
27-0.081937-0.66570.253973
280.0236720.19230.424043
29-0.082847-0.6730.251633
300.0772580.62760.266201
31-0.081979-0.6660.253865
320.010020.08140.467685
33-0.048397-0.39320.347726
340.0061620.05010.480114
35-0.094255-0.76570.223284
36-0.043126-0.35040.363593

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.148273 & 1.2046 & 0.116335 \tabularnewline
2 & -0.17743 & -1.4415 & 0.077093 \tabularnewline
3 & -0.13455 & -1.0931 & 0.139164 \tabularnewline
4 & -0.162277 & -1.3183 & 0.095973 \tabularnewline
5 & 0.120438 & 0.9784 & 0.165713 \tabularnewline
6 & 0.122865 & 0.9982 & 0.160924 \tabularnewline
7 & 0.066118 & 0.5371 & 0.296488 \tabularnewline
8 & -0.166234 & -1.3505 & 0.090736 \tabularnewline
9 & -0.058843 & -0.478 & 0.317099 \tabularnewline
10 & -0.170902 & -1.3884 & 0.08484 \tabularnewline
11 & 0.158982 & 1.2916 & 0.100505 \tabularnewline
12 & 0.624012 & 5.0695 & 2e-06 \tabularnewline
13 & -0.261332 & -2.1231 & 0.018751 \tabularnewline
14 & -0.026084 & -0.2119 & 0.416415 \tabularnewline
15 & -0.039474 & -0.3207 & 0.374729 \tabularnewline
16 & -0.071631 & -0.5819 & 0.281298 \tabularnewline
17 & -0.05193 & -0.4219 & 0.337243 \tabularnewline
18 & -0.183949 & -1.4944 & 0.069917 \tabularnewline
19 & -0.071009 & -0.5769 & 0.282991 \tabularnewline
20 & -0.09635 & -0.7828 & 0.218287 \tabularnewline
21 & -0.001916 & -0.0156 & 0.493814 \tabularnewline
22 & 0.032358 & 0.2629 & 0.396731 \tabularnewline
23 & -0.152827 & -1.2416 & 0.109395 \tabularnewline
24 & 0.033475 & 0.272 & 0.393254 \tabularnewline
25 & -0.011187 & -0.0909 & 0.463932 \tabularnewline
26 & -0.044649 & -0.3627 & 0.358983 \tabularnewline
27 & -0.081937 & -0.6657 & 0.253973 \tabularnewline
28 & 0.023672 & 0.1923 & 0.424043 \tabularnewline
29 & -0.082847 & -0.673 & 0.251633 \tabularnewline
30 & 0.077258 & 0.6276 & 0.266201 \tabularnewline
31 & -0.081979 & -0.666 & 0.253865 \tabularnewline
32 & 0.01002 & 0.0814 & 0.467685 \tabularnewline
33 & -0.048397 & -0.3932 & 0.347726 \tabularnewline
34 & 0.006162 & 0.0501 & 0.480114 \tabularnewline
35 & -0.094255 & -0.7657 & 0.223284 \tabularnewline
36 & -0.043126 & -0.3504 & 0.363593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62820&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]0.148273[/C][C]1.2046[/C][C]0.116335[/C][/ROW]
[ROW][C]2[/C][C]-0.17743[/C][C]-1.4415[/C][C]0.077093[/C][/ROW]
[ROW][C]3[/C][C]-0.13455[/C][C]-1.0931[/C][C]0.139164[/C][/ROW]
[ROW][C]4[/C][C]-0.162277[/C][C]-1.3183[/C][C]0.095973[/C][/ROW]
[ROW][C]5[/C][C]0.120438[/C][C]0.9784[/C][C]0.165713[/C][/ROW]
[ROW][C]6[/C][C]0.122865[/C][C]0.9982[/C][C]0.160924[/C][/ROW]
[ROW][C]7[/C][C]0.066118[/C][C]0.5371[/C][C]0.296488[/C][/ROW]
[ROW][C]8[/C][C]-0.166234[/C][C]-1.3505[/C][C]0.090736[/C][/ROW]
[ROW][C]9[/C][C]-0.058843[/C][C]-0.478[/C][C]0.317099[/C][/ROW]
[ROW][C]10[/C][C]-0.170902[/C][C]-1.3884[/C][C]0.08484[/C][/ROW]
[ROW][C]11[/C][C]0.158982[/C][C]1.2916[/C][C]0.100505[/C][/ROW]
[ROW][C]12[/C][C]0.624012[/C][C]5.0695[/C][C]2e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.261332[/C][C]-2.1231[/C][C]0.018751[/C][/ROW]
[ROW][C]14[/C][C]-0.026084[/C][C]-0.2119[/C][C]0.416415[/C][/ROW]
[ROW][C]15[/C][C]-0.039474[/C][C]-0.3207[/C][C]0.374729[/C][/ROW]
[ROW][C]16[/C][C]-0.071631[/C][C]-0.5819[/C][C]0.281298[/C][/ROW]
[ROW][C]17[/C][C]-0.05193[/C][C]-0.4219[/C][C]0.337243[/C][/ROW]
[ROW][C]18[/C][C]-0.183949[/C][C]-1.4944[/C][C]0.069917[/C][/ROW]
[ROW][C]19[/C][C]-0.071009[/C][C]-0.5769[/C][C]0.282991[/C][/ROW]
[ROW][C]20[/C][C]-0.09635[/C][C]-0.7828[/C][C]0.218287[/C][/ROW]
[ROW][C]21[/C][C]-0.001916[/C][C]-0.0156[/C][C]0.493814[/C][/ROW]
[ROW][C]22[/C][C]0.032358[/C][C]0.2629[/C][C]0.396731[/C][/ROW]
[ROW][C]23[/C][C]-0.152827[/C][C]-1.2416[/C][C]0.109395[/C][/ROW]
[ROW][C]24[/C][C]0.033475[/C][C]0.272[/C][C]0.393254[/C][/ROW]
[ROW][C]25[/C][C]-0.011187[/C][C]-0.0909[/C][C]0.463932[/C][/ROW]
[ROW][C]26[/C][C]-0.044649[/C][C]-0.3627[/C][C]0.358983[/C][/ROW]
[ROW][C]27[/C][C]-0.081937[/C][C]-0.6657[/C][C]0.253973[/C][/ROW]
[ROW][C]28[/C][C]0.023672[/C][C]0.1923[/C][C]0.424043[/C][/ROW]
[ROW][C]29[/C][C]-0.082847[/C][C]-0.673[/C][C]0.251633[/C][/ROW]
[ROW][C]30[/C][C]0.077258[/C][C]0.6276[/C][C]0.266201[/C][/ROW]
[ROW][C]31[/C][C]-0.081979[/C][C]-0.666[/C][C]0.253865[/C][/ROW]
[ROW][C]32[/C][C]0.01002[/C][C]0.0814[/C][C]0.467685[/C][/ROW]
[ROW][C]33[/C][C]-0.048397[/C][C]-0.3932[/C][C]0.347726[/C][/ROW]
[ROW][C]34[/C][C]0.006162[/C][C]0.0501[/C][C]0.480114[/C][/ROW]
[ROW][C]35[/C][C]-0.094255[/C][C]-0.7657[/C][C]0.223284[/C][/ROW]
[ROW][C]36[/C][C]-0.043126[/C][C]-0.3504[/C][C]0.363593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62820&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62820&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
10.1482731.20460.116335
2-0.17743-1.44150.077093
3-0.13455-1.09310.139164
4-0.162277-1.31830.095973
50.1204380.97840.165713
60.1228650.99820.160924
70.0661180.53710.296488
8-0.166234-1.35050.090736
9-0.058843-0.4780.317099
10-0.170902-1.38840.08484
110.1589821.29160.100505
120.6240125.06952e-06
13-0.261332-2.12310.018751
14-0.026084-0.21190.416415
15-0.039474-0.32070.374729
16-0.071631-0.58190.281298
17-0.05193-0.42190.337243
18-0.183949-1.49440.069917
19-0.071009-0.57690.282991
20-0.09635-0.78280.218287
21-0.001916-0.01560.493814
220.0323580.26290.396731
23-0.152827-1.24160.109395
240.0334750.2720.393254
25-0.011187-0.09090.463932
26-0.044649-0.36270.358983
27-0.081937-0.66570.253973
280.0236720.19230.424043
29-0.082847-0.6730.251633
300.0772580.62760.266201
31-0.081979-0.6660.253865
320.010020.08140.467685
33-0.048397-0.39320.347726
340.0061620.05010.480114
35-0.094255-0.76570.223284
36-0.043126-0.35040.363593


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')