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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 03:36:07 -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/t1259836647bu9jzvcx77tkji2.htm/, Retrieved Thu, 28 Mar 2024 10:08:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62670, Retrieved Thu, 28 Mar 2024 10:08:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [] [2009-12-03 10:03:52] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P       [(Partial) Autocorrelation Function] [] [2009-12-03 10:05:50] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 10:36:07] [5858ea01c9bd81debbf921a11363ad90] [Current]
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Dataseries X:
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730




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=62670&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=62670&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62670&T=0

As an alternative you can also use a 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
10.5107735.03051e-06
20.4325774.26042.4e-05
30.229922.26450.012886
40.1206541.18830.118807
50.1098181.08160.141059
60.088010.86680.194095
70.0128060.12610.449947
80.0438660.4320.333338
9-0.041761-0.41130.34088
10-0.257818-2.53920.00635
11-0.380343-3.74590.000153
12-0.525976-5.18031e-06
13-0.429473-4.22982.7e-05
14-0.27126-2.67160.004427
15-0.122688-1.20830.114927
16-0.13888-1.36780.087266
17-0.073717-0.7260.234784
18-0.047283-0.46570.321244
19-0.08374-0.82470.20577
20-0.033547-0.33040.370906
210.023230.22880.409757
220.0619450.61010.271614
230.3303983.2540.000783
240.2916272.87220.002503
250.3152793.10510.001247
260.2074222.04290.021889
270.0751870.74050.230391
280.0212380.20920.417377
290.0576060.56730.285894
30-0.060275-0.59360.277067
310.0042530.04190.483337
32-0.035945-0.3540.362047
33-0.058293-0.57410.283607
34-0.121493-1.19660.117196
35-0.224648-2.21250.014638
36-0.325964-3.21040.000899

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.510773 & 5.0305 & 1e-06 \tabularnewline
2 & 0.432577 & 4.2604 & 2.4e-05 \tabularnewline
3 & 0.22992 & 2.2645 & 0.012886 \tabularnewline
4 & 0.120654 & 1.1883 & 0.118807 \tabularnewline
5 & 0.109818 & 1.0816 & 0.141059 \tabularnewline
6 & 0.08801 & 0.8668 & 0.194095 \tabularnewline
7 & 0.012806 & 0.1261 & 0.449947 \tabularnewline
8 & 0.043866 & 0.432 & 0.333338 \tabularnewline
9 & -0.041761 & -0.4113 & 0.34088 \tabularnewline
10 & -0.257818 & -2.5392 & 0.00635 \tabularnewline
11 & -0.380343 & -3.7459 & 0.000153 \tabularnewline
12 & -0.525976 & -5.1803 & 1e-06 \tabularnewline
13 & -0.429473 & -4.2298 & 2.7e-05 \tabularnewline
14 & -0.27126 & -2.6716 & 0.004427 \tabularnewline
15 & -0.122688 & -1.2083 & 0.114927 \tabularnewline
16 & -0.13888 & -1.3678 & 0.087266 \tabularnewline
17 & -0.073717 & -0.726 & 0.234784 \tabularnewline
18 & -0.047283 & -0.4657 & 0.321244 \tabularnewline
19 & -0.08374 & -0.8247 & 0.20577 \tabularnewline
20 & -0.033547 & -0.3304 & 0.370906 \tabularnewline
21 & 0.02323 & 0.2288 & 0.409757 \tabularnewline
22 & 0.061945 & 0.6101 & 0.271614 \tabularnewline
23 & 0.330398 & 3.254 & 0.000783 \tabularnewline
24 & 0.291627 & 2.8722 & 0.002503 \tabularnewline
25 & 0.315279 & 3.1051 & 0.001247 \tabularnewline
26 & 0.207422 & 2.0429 & 0.021889 \tabularnewline
27 & 0.075187 & 0.7405 & 0.230391 \tabularnewline
28 & 0.021238 & 0.2092 & 0.417377 \tabularnewline
29 & 0.057606 & 0.5673 & 0.285894 \tabularnewline
30 & -0.060275 & -0.5936 & 0.277067 \tabularnewline
31 & 0.004253 & 0.0419 & 0.483337 \tabularnewline
32 & -0.035945 & -0.354 & 0.362047 \tabularnewline
33 & -0.058293 & -0.5741 & 0.283607 \tabularnewline
34 & -0.121493 & -1.1966 & 0.117196 \tabularnewline
35 & -0.224648 & -2.2125 & 0.014638 \tabularnewline
36 & -0.325964 & -3.2104 & 0.000899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62670&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]0.510773[/C][C]5.0305[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.432577[/C][C]4.2604[/C][C]2.4e-05[/C][/ROW]
[ROW][C]3[/C][C]0.22992[/C][C]2.2645[/C][C]0.012886[/C][/ROW]
[ROW][C]4[/C][C]0.120654[/C][C]1.1883[/C][C]0.118807[/C][/ROW]
[ROW][C]5[/C][C]0.109818[/C][C]1.0816[/C][C]0.141059[/C][/ROW]
[ROW][C]6[/C][C]0.08801[/C][C]0.8668[/C][C]0.194095[/C][/ROW]
[ROW][C]7[/C][C]0.012806[/C][C]0.1261[/C][C]0.449947[/C][/ROW]
[ROW][C]8[/C][C]0.043866[/C][C]0.432[/C][C]0.333338[/C][/ROW]
[ROW][C]9[/C][C]-0.041761[/C][C]-0.4113[/C][C]0.34088[/C][/ROW]
[ROW][C]10[/C][C]-0.257818[/C][C]-2.5392[/C][C]0.00635[/C][/ROW]
[ROW][C]11[/C][C]-0.380343[/C][C]-3.7459[/C][C]0.000153[/C][/ROW]
[ROW][C]12[/C][C]-0.525976[/C][C]-5.1803[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.429473[/C][C]-4.2298[/C][C]2.7e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.27126[/C][C]-2.6716[/C][C]0.004427[/C][/ROW]
[ROW][C]15[/C][C]-0.122688[/C][C]-1.2083[/C][C]0.114927[/C][/ROW]
[ROW][C]16[/C][C]-0.13888[/C][C]-1.3678[/C][C]0.087266[/C][/ROW]
[ROW][C]17[/C][C]-0.073717[/C][C]-0.726[/C][C]0.234784[/C][/ROW]
[ROW][C]18[/C][C]-0.047283[/C][C]-0.4657[/C][C]0.321244[/C][/ROW]
[ROW][C]19[/C][C]-0.08374[/C][C]-0.8247[/C][C]0.20577[/C][/ROW]
[ROW][C]20[/C][C]-0.033547[/C][C]-0.3304[/C][C]0.370906[/C][/ROW]
[ROW][C]21[/C][C]0.02323[/C][C]0.2288[/C][C]0.409757[/C][/ROW]
[ROW][C]22[/C][C]0.061945[/C][C]0.6101[/C][C]0.271614[/C][/ROW]
[ROW][C]23[/C][C]0.330398[/C][C]3.254[/C][C]0.000783[/C][/ROW]
[ROW][C]24[/C][C]0.291627[/C][C]2.8722[/C][C]0.002503[/C][/ROW]
[ROW][C]25[/C][C]0.315279[/C][C]3.1051[/C][C]0.001247[/C][/ROW]
[ROW][C]26[/C][C]0.207422[/C][C]2.0429[/C][C]0.021889[/C][/ROW]
[ROW][C]27[/C][C]0.075187[/C][C]0.7405[/C][C]0.230391[/C][/ROW]
[ROW][C]28[/C][C]0.021238[/C][C]0.2092[/C][C]0.417377[/C][/ROW]
[ROW][C]29[/C][C]0.057606[/C][C]0.5673[/C][C]0.285894[/C][/ROW]
[ROW][C]30[/C][C]-0.060275[/C][C]-0.5936[/C][C]0.277067[/C][/ROW]
[ROW][C]31[/C][C]0.004253[/C][C]0.0419[/C][C]0.483337[/C][/ROW]
[ROW][C]32[/C][C]-0.035945[/C][C]-0.354[/C][C]0.362047[/C][/ROW]
[ROW][C]33[/C][C]-0.058293[/C][C]-0.5741[/C][C]0.283607[/C][/ROW]
[ROW][C]34[/C][C]-0.121493[/C][C]-1.1966[/C][C]0.117196[/C][/ROW]
[ROW][C]35[/C][C]-0.224648[/C][C]-2.2125[/C][C]0.014638[/C][/ROW]
[ROW][C]36[/C][C]-0.325964[/C][C]-3.2104[/C][C]0.000899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62670&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62670&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5107735.03051e-06
20.4325774.26042.4e-05
30.229922.26450.012886
40.1206541.18830.118807
50.1098181.08160.141059
60.088010.86680.194095
70.0128060.12610.449947
80.0438660.4320.333338
9-0.041761-0.41130.34088
10-0.257818-2.53920.00635
11-0.380343-3.74590.000153
12-0.525976-5.18031e-06
13-0.429473-4.22982.7e-05
14-0.27126-2.67160.004427
15-0.122688-1.20830.114927
16-0.13888-1.36780.087266
17-0.073717-0.7260.234784
18-0.047283-0.46570.321244
19-0.08374-0.82470.20577
20-0.033547-0.33040.370906
210.023230.22880.409757
220.0619450.61010.271614
230.3303983.2540.000783
240.2916272.87220.002503
250.3152793.10510.001247
260.2074222.04290.021889
270.0751870.74050.230391
280.0212380.20920.417377
290.0576060.56730.285894
30-0.060275-0.59360.277067
310.0042530.04190.483337
32-0.035945-0.3540.362047
33-0.058293-0.57410.283607
34-0.121493-1.19660.117196
35-0.224648-2.21250.014638
36-0.325964-3.21040.000899







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5107735.03051e-06
20.232292.28780.012161
3-0.083451-0.82190.206576
4-0.066211-0.65210.257938
50.0781110.76930.22179
60.0417630.41130.340873
7-0.099763-0.98260.164136
80.0451280.44450.32885
9-0.062873-0.61920.26861
10-0.348661-3.43390.000438
11-0.258625-2.54720.006216
12-0.2303-2.26820.012767
130.0115140.11340.454973
140.1555071.53160.064442
150.1932231.9030.030001
16-0.092097-0.90710.183314
17-0.027611-0.27190.393126
180.1304031.28430.101044
19-0.043124-0.42470.33599
20-0.009182-0.09040.464065
210.0621850.61250.270836
22-0.181859-1.79110.038198
230.1247621.22880.111067
24-0.025892-0.2550.399628
250.063420.62460.266844
26-0.022393-0.22050.412954
27-0.06932-0.68270.248203
28-0.103349-1.01790.155635
290.0332310.32730.372077
30-0.098353-0.96870.167561
31-0.007207-0.0710.471778
32-0.081507-0.80280.21204
330.0313540.30880.379067
34-0.037114-0.36550.357755
350.0494630.48720.313625
36-0.087635-0.86310.195105

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.510773 & 5.0305 & 1e-06 \tabularnewline
2 & 0.23229 & 2.2878 & 0.012161 \tabularnewline
3 & -0.083451 & -0.8219 & 0.206576 \tabularnewline
4 & -0.066211 & -0.6521 & 0.257938 \tabularnewline
5 & 0.078111 & 0.7693 & 0.22179 \tabularnewline
6 & 0.041763 & 0.4113 & 0.340873 \tabularnewline
7 & -0.099763 & -0.9826 & 0.164136 \tabularnewline
8 & 0.045128 & 0.4445 & 0.32885 \tabularnewline
9 & -0.062873 & -0.6192 & 0.26861 \tabularnewline
10 & -0.348661 & -3.4339 & 0.000438 \tabularnewline
11 & -0.258625 & -2.5472 & 0.006216 \tabularnewline
12 & -0.2303 & -2.2682 & 0.012767 \tabularnewline
13 & 0.011514 & 0.1134 & 0.454973 \tabularnewline
14 & 0.155507 & 1.5316 & 0.064442 \tabularnewline
15 & 0.193223 & 1.903 & 0.030001 \tabularnewline
16 & -0.092097 & -0.9071 & 0.183314 \tabularnewline
17 & -0.027611 & -0.2719 & 0.393126 \tabularnewline
18 & 0.130403 & 1.2843 & 0.101044 \tabularnewline
19 & -0.043124 & -0.4247 & 0.33599 \tabularnewline
20 & -0.009182 & -0.0904 & 0.464065 \tabularnewline
21 & 0.062185 & 0.6125 & 0.270836 \tabularnewline
22 & -0.181859 & -1.7911 & 0.038198 \tabularnewline
23 & 0.124762 & 1.2288 & 0.111067 \tabularnewline
24 & -0.025892 & -0.255 & 0.399628 \tabularnewline
25 & 0.06342 & 0.6246 & 0.266844 \tabularnewline
26 & -0.022393 & -0.2205 & 0.412954 \tabularnewline
27 & -0.06932 & -0.6827 & 0.248203 \tabularnewline
28 & -0.103349 & -1.0179 & 0.155635 \tabularnewline
29 & 0.033231 & 0.3273 & 0.372077 \tabularnewline
30 & -0.098353 & -0.9687 & 0.167561 \tabularnewline
31 & -0.007207 & -0.071 & 0.471778 \tabularnewline
32 & -0.081507 & -0.8028 & 0.21204 \tabularnewline
33 & 0.031354 & 0.3088 & 0.379067 \tabularnewline
34 & -0.037114 & -0.3655 & 0.357755 \tabularnewline
35 & 0.049463 & 0.4872 & 0.313625 \tabularnewline
36 & -0.087635 & -0.8631 & 0.195105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62670&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]0.510773[/C][C]5.0305[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.23229[/C][C]2.2878[/C][C]0.012161[/C][/ROW]
[ROW][C]3[/C][C]-0.083451[/C][C]-0.8219[/C][C]0.206576[/C][/ROW]
[ROW][C]4[/C][C]-0.066211[/C][C]-0.6521[/C][C]0.257938[/C][/ROW]
[ROW][C]5[/C][C]0.078111[/C][C]0.7693[/C][C]0.22179[/C][/ROW]
[ROW][C]6[/C][C]0.041763[/C][C]0.4113[/C][C]0.340873[/C][/ROW]
[ROW][C]7[/C][C]-0.099763[/C][C]-0.9826[/C][C]0.164136[/C][/ROW]
[ROW][C]8[/C][C]0.045128[/C][C]0.4445[/C][C]0.32885[/C][/ROW]
[ROW][C]9[/C][C]-0.062873[/C][C]-0.6192[/C][C]0.26861[/C][/ROW]
[ROW][C]10[/C][C]-0.348661[/C][C]-3.4339[/C][C]0.000438[/C][/ROW]
[ROW][C]11[/C][C]-0.258625[/C][C]-2.5472[/C][C]0.006216[/C][/ROW]
[ROW][C]12[/C][C]-0.2303[/C][C]-2.2682[/C][C]0.012767[/C][/ROW]
[ROW][C]13[/C][C]0.011514[/C][C]0.1134[/C][C]0.454973[/C][/ROW]
[ROW][C]14[/C][C]0.155507[/C][C]1.5316[/C][C]0.064442[/C][/ROW]
[ROW][C]15[/C][C]0.193223[/C][C]1.903[/C][C]0.030001[/C][/ROW]
[ROW][C]16[/C][C]-0.092097[/C][C]-0.9071[/C][C]0.183314[/C][/ROW]
[ROW][C]17[/C][C]-0.027611[/C][C]-0.2719[/C][C]0.393126[/C][/ROW]
[ROW][C]18[/C][C]0.130403[/C][C]1.2843[/C][C]0.101044[/C][/ROW]
[ROW][C]19[/C][C]-0.043124[/C][C]-0.4247[/C][C]0.33599[/C][/ROW]
[ROW][C]20[/C][C]-0.009182[/C][C]-0.0904[/C][C]0.464065[/C][/ROW]
[ROW][C]21[/C][C]0.062185[/C][C]0.6125[/C][C]0.270836[/C][/ROW]
[ROW][C]22[/C][C]-0.181859[/C][C]-1.7911[/C][C]0.038198[/C][/ROW]
[ROW][C]23[/C][C]0.124762[/C][C]1.2288[/C][C]0.111067[/C][/ROW]
[ROW][C]24[/C][C]-0.025892[/C][C]-0.255[/C][C]0.399628[/C][/ROW]
[ROW][C]25[/C][C]0.06342[/C][C]0.6246[/C][C]0.266844[/C][/ROW]
[ROW][C]26[/C][C]-0.022393[/C][C]-0.2205[/C][C]0.412954[/C][/ROW]
[ROW][C]27[/C][C]-0.06932[/C][C]-0.6827[/C][C]0.248203[/C][/ROW]
[ROW][C]28[/C][C]-0.103349[/C][C]-1.0179[/C][C]0.155635[/C][/ROW]
[ROW][C]29[/C][C]0.033231[/C][C]0.3273[/C][C]0.372077[/C][/ROW]
[ROW][C]30[/C][C]-0.098353[/C][C]-0.9687[/C][C]0.167561[/C][/ROW]
[ROW][C]31[/C][C]-0.007207[/C][C]-0.071[/C][C]0.471778[/C][/ROW]
[ROW][C]32[/C][C]-0.081507[/C][C]-0.8028[/C][C]0.21204[/C][/ROW]
[ROW][C]33[/C][C]0.031354[/C][C]0.3088[/C][C]0.379067[/C][/ROW]
[ROW][C]34[/C][C]-0.037114[/C][C]-0.3655[/C][C]0.357755[/C][/ROW]
[ROW][C]35[/C][C]0.049463[/C][C]0.4872[/C][C]0.313625[/C][/ROW]
[ROW][C]36[/C][C]-0.087635[/C][C]-0.8631[/C][C]0.195105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62670&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62670&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5107735.03051e-06
20.232292.28780.012161
3-0.083451-0.82190.206576
4-0.066211-0.65210.257938
50.0781110.76930.22179
60.0417630.41130.340873
7-0.099763-0.98260.164136
80.0451280.44450.32885
9-0.062873-0.61920.26861
10-0.348661-3.43390.000438
11-0.258625-2.54720.006216
12-0.2303-2.26820.012767
130.0115140.11340.454973
140.1555071.53160.064442
150.1932231.9030.030001
16-0.092097-0.90710.183314
17-0.027611-0.27190.393126
180.1304031.28430.101044
19-0.043124-0.42470.33599
20-0.009182-0.09040.464065
210.0621850.61250.270836
22-0.181859-1.79110.038198
230.1247621.22880.111067
24-0.025892-0.2550.399628
250.063420.62460.266844
26-0.022393-0.22050.412954
27-0.06932-0.68270.248203
28-0.103349-1.01790.155635
290.0332310.32730.372077
30-0.098353-0.96870.167561
31-0.007207-0.0710.471778
32-0.081507-0.80280.21204
330.0313540.30880.379067
34-0.037114-0.36550.357755
350.0494630.48720.313625
36-0.087635-0.86310.195105



Parameters (Session):
par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
Parameters (R input):
par1 = 36 ; par2 = 1.0 ; par3 = 0 ; 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')