Free Statistics

of Irreproducible Research!

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 03:11:39 -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/26/t12592303419l6ues83x9jitw5.htm/, Retrieved Sun, 28 Apr 2024 21:06:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59771, Retrieved Sun, 28 Apr 2024 21:06:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [ACF met: d=0, D=0...] [2009-11-26 10:08:37] [34d27ebe78dc2d31581e8710befe8733]
-                 [(Partial) Autocorrelation Function] [ACF met: d=0, D=1...] [2009-11-26 10:11:39] [371dc2189c569d90e2c1567f632c3ec0] [Current]
-                   [(Partial) Autocorrelation Function] [ACF met: d=1, D=0...] [2009-12-19 11:10:28] [34d27ebe78dc2d31581e8710befe8733]
Feedback Forum

Post a new message
Dataseries X:
1919
1911
1870
2263
1802
1863
1989
2197
2409
2502
2593
2598
2053
2213
2238
2359
2151
2474
3079
2312
2565
1972
2484
2202
2151
1976
2012
2114
1772
1957
2070
1990
2182
2008
1916
2397
2114
1778
1641
2186
1773
1785
2217
2153
1895
2475
1793
2308
2051
1898
2142
1874
1560
1808
1575
1525
1997
1753
1623
2251
1890




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=59771&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=59771&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59771&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
10.3372012.36040.01114
20.3699722.58980.006305
30.2386191.67030.050615
40.1927621.34930.091716
50.0236630.16560.43456
60.0838780.58710.279902
70.0013560.00950.496234
8-0.017343-0.12140.451935
9-0.102278-0.71590.238711
10-0.135397-0.94780.173947
11-0.15293-1.07050.144818
12-0.423724-2.96610.002326
13-0.229047-1.60330.057645
14-0.224585-1.57210.061182
15-0.216916-1.51840.067669
16-0.239851-1.6790.049763
17-0.06095-0.42670.335751
18-0.128983-0.90290.185503
19-0.098528-0.68970.24682
20-0.148705-1.04090.151507
210.0099330.06950.472424
22-0.048441-0.33910.367997
230.1047180.7330.233518
240.051510.36060.359986
250.1910251.33720.09367
260.1015310.71070.240316
270.1789921.25290.108087
280.1187130.8310.205006
290.0833170.58320.281211
300.0821780.57520.283879
310.1132330.79260.215908
320.1798011.25860.107068
330.0655260.45870.324245
340.0434010.30380.381281
35-0.018991-0.13290.447395
36-0.01992-0.13940.444836

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.337201 & 2.3604 & 0.01114 \tabularnewline
2 & 0.369972 & 2.5898 & 0.006305 \tabularnewline
3 & 0.238619 & 1.6703 & 0.050615 \tabularnewline
4 & 0.192762 & 1.3493 & 0.091716 \tabularnewline
5 & 0.023663 & 0.1656 & 0.43456 \tabularnewline
6 & 0.083878 & 0.5871 & 0.279902 \tabularnewline
7 & 0.001356 & 0.0095 & 0.496234 \tabularnewline
8 & -0.017343 & -0.1214 & 0.451935 \tabularnewline
9 & -0.102278 & -0.7159 & 0.238711 \tabularnewline
10 & -0.135397 & -0.9478 & 0.173947 \tabularnewline
11 & -0.15293 & -1.0705 & 0.144818 \tabularnewline
12 & -0.423724 & -2.9661 & 0.002326 \tabularnewline
13 & -0.229047 & -1.6033 & 0.057645 \tabularnewline
14 & -0.224585 & -1.5721 & 0.061182 \tabularnewline
15 & -0.216916 & -1.5184 & 0.067669 \tabularnewline
16 & -0.239851 & -1.679 & 0.049763 \tabularnewline
17 & -0.06095 & -0.4267 & 0.335751 \tabularnewline
18 & -0.128983 & -0.9029 & 0.185503 \tabularnewline
19 & -0.098528 & -0.6897 & 0.24682 \tabularnewline
20 & -0.148705 & -1.0409 & 0.151507 \tabularnewline
21 & 0.009933 & 0.0695 & 0.472424 \tabularnewline
22 & -0.048441 & -0.3391 & 0.367997 \tabularnewline
23 & 0.104718 & 0.733 & 0.233518 \tabularnewline
24 & 0.05151 & 0.3606 & 0.359986 \tabularnewline
25 & 0.191025 & 1.3372 & 0.09367 \tabularnewline
26 & 0.101531 & 0.7107 & 0.240316 \tabularnewline
27 & 0.178992 & 1.2529 & 0.108087 \tabularnewline
28 & 0.118713 & 0.831 & 0.205006 \tabularnewline
29 & 0.083317 & 0.5832 & 0.281211 \tabularnewline
30 & 0.082178 & 0.5752 & 0.283879 \tabularnewline
31 & 0.113233 & 0.7926 & 0.215908 \tabularnewline
32 & 0.179801 & 1.2586 & 0.107068 \tabularnewline
33 & 0.065526 & 0.4587 & 0.324245 \tabularnewline
34 & 0.043401 & 0.3038 & 0.381281 \tabularnewline
35 & -0.018991 & -0.1329 & 0.447395 \tabularnewline
36 & -0.01992 & -0.1394 & 0.444836 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59771&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]0.337201[/C][C]2.3604[/C][C]0.01114[/C][/ROW]
[ROW][C]2[/C][C]0.369972[/C][C]2.5898[/C][C]0.006305[/C][/ROW]
[ROW][C]3[/C][C]0.238619[/C][C]1.6703[/C][C]0.050615[/C][/ROW]
[ROW][C]4[/C][C]0.192762[/C][C]1.3493[/C][C]0.091716[/C][/ROW]
[ROW][C]5[/C][C]0.023663[/C][C]0.1656[/C][C]0.43456[/C][/ROW]
[ROW][C]6[/C][C]0.083878[/C][C]0.5871[/C][C]0.279902[/C][/ROW]
[ROW][C]7[/C][C]0.001356[/C][C]0.0095[/C][C]0.496234[/C][/ROW]
[ROW][C]8[/C][C]-0.017343[/C][C]-0.1214[/C][C]0.451935[/C][/ROW]
[ROW][C]9[/C][C]-0.102278[/C][C]-0.7159[/C][C]0.238711[/C][/ROW]
[ROW][C]10[/C][C]-0.135397[/C][C]-0.9478[/C][C]0.173947[/C][/ROW]
[ROW][C]11[/C][C]-0.15293[/C][C]-1.0705[/C][C]0.144818[/C][/ROW]
[ROW][C]12[/C][C]-0.423724[/C][C]-2.9661[/C][C]0.002326[/C][/ROW]
[ROW][C]13[/C][C]-0.229047[/C][C]-1.6033[/C][C]0.057645[/C][/ROW]
[ROW][C]14[/C][C]-0.224585[/C][C]-1.5721[/C][C]0.061182[/C][/ROW]
[ROW][C]15[/C][C]-0.216916[/C][C]-1.5184[/C][C]0.067669[/C][/ROW]
[ROW][C]16[/C][C]-0.239851[/C][C]-1.679[/C][C]0.049763[/C][/ROW]
[ROW][C]17[/C][C]-0.06095[/C][C]-0.4267[/C][C]0.335751[/C][/ROW]
[ROW][C]18[/C][C]-0.128983[/C][C]-0.9029[/C][C]0.185503[/C][/ROW]
[ROW][C]19[/C][C]-0.098528[/C][C]-0.6897[/C][C]0.24682[/C][/ROW]
[ROW][C]20[/C][C]-0.148705[/C][C]-1.0409[/C][C]0.151507[/C][/ROW]
[ROW][C]21[/C][C]0.009933[/C][C]0.0695[/C][C]0.472424[/C][/ROW]
[ROW][C]22[/C][C]-0.048441[/C][C]-0.3391[/C][C]0.367997[/C][/ROW]
[ROW][C]23[/C][C]0.104718[/C][C]0.733[/C][C]0.233518[/C][/ROW]
[ROW][C]24[/C][C]0.05151[/C][C]0.3606[/C][C]0.359986[/C][/ROW]
[ROW][C]25[/C][C]0.191025[/C][C]1.3372[/C][C]0.09367[/C][/ROW]
[ROW][C]26[/C][C]0.101531[/C][C]0.7107[/C][C]0.240316[/C][/ROW]
[ROW][C]27[/C][C]0.178992[/C][C]1.2529[/C][C]0.108087[/C][/ROW]
[ROW][C]28[/C][C]0.118713[/C][C]0.831[/C][C]0.205006[/C][/ROW]
[ROW][C]29[/C][C]0.083317[/C][C]0.5832[/C][C]0.281211[/C][/ROW]
[ROW][C]30[/C][C]0.082178[/C][C]0.5752[/C][C]0.283879[/C][/ROW]
[ROW][C]31[/C][C]0.113233[/C][C]0.7926[/C][C]0.215908[/C][/ROW]
[ROW][C]32[/C][C]0.179801[/C][C]1.2586[/C][C]0.107068[/C][/ROW]
[ROW][C]33[/C][C]0.065526[/C][C]0.4587[/C][C]0.324245[/C][/ROW]
[ROW][C]34[/C][C]0.043401[/C][C]0.3038[/C][C]0.381281[/C][/ROW]
[ROW][C]35[/C][C]-0.018991[/C][C]-0.1329[/C][C]0.447395[/C][/ROW]
[ROW][C]36[/C][C]-0.01992[/C][C]-0.1394[/C][C]0.444836[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59771&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59771&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
10.3372012.36040.01114
20.3699722.58980.006305
30.2386191.67030.050615
40.1927621.34930.091716
50.0236630.16560.43456
60.0838780.58710.279902
70.0013560.00950.496234
8-0.017343-0.12140.451935
9-0.102278-0.71590.238711
10-0.135397-0.94780.173947
11-0.15293-1.07050.144818
12-0.423724-2.96610.002326
13-0.229047-1.60330.057645
14-0.224585-1.57210.061182
15-0.216916-1.51840.067669
16-0.239851-1.6790.049763
17-0.06095-0.42670.335751
18-0.128983-0.90290.185503
19-0.098528-0.68970.24682
20-0.148705-1.04090.151507
210.0099330.06950.472424
22-0.048441-0.33910.367997
230.1047180.7330.233518
240.051510.36060.359986
250.1910251.33720.09367
260.1015310.71070.240316
270.1789921.25290.108087
280.1187130.8310.205006
290.0833170.58320.281211
300.0821780.57520.283879
310.1132330.79260.215908
320.1798011.25860.107068
330.0655260.45870.324245
340.0434010.30380.381281
35-0.018991-0.13290.447395
36-0.01992-0.13940.444836







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3372012.36040.01114
20.2891442.0240.02422
30.0645610.45190.326658
40.0210180.14710.441818
5-0.138371-0.96860.168752
60.0376580.26360.396595
7-0.013163-0.09210.46348
8-0.03449-0.24140.405114
9-0.09937-0.69560.244986
10-0.1096-0.76720.223321
11-0.037936-0.26550.39585
12-0.373487-2.61440.005921
130.0282810.1980.421946
140.0684830.47940.3169
15-0.036638-0.25650.399332
16-0.09395-0.65770.25692
170.0497090.3480.36468
180.0104050.07280.471116
19-0.075691-0.52980.299308
20-0.132399-0.92680.179289
210.0740880.51860.303182
22-0.01388-0.09720.461497
230.1144760.80130.213405
24-0.181496-1.27050.104958
250.1178810.82520.206638
260.0305160.21360.415868
270.0042980.03010.488061
28-0.086168-0.60320.274587
29-0.025154-0.17610.43048
300.0696230.48740.314087
31-0.011062-0.07740.469296
320.0718540.5030.308617
33-0.005457-0.03820.484843
34-0.11104-0.77730.220365
350.009970.06980.472324
36-0.101377-0.70960.240646

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.337201 & 2.3604 & 0.01114 \tabularnewline
2 & 0.289144 & 2.024 & 0.02422 \tabularnewline
3 & 0.064561 & 0.4519 & 0.326658 \tabularnewline
4 & 0.021018 & 0.1471 & 0.441818 \tabularnewline
5 & -0.138371 & -0.9686 & 0.168752 \tabularnewline
6 & 0.037658 & 0.2636 & 0.396595 \tabularnewline
7 & -0.013163 & -0.0921 & 0.46348 \tabularnewline
8 & -0.03449 & -0.2414 & 0.405114 \tabularnewline
9 & -0.09937 & -0.6956 & 0.244986 \tabularnewline
10 & -0.1096 & -0.7672 & 0.223321 \tabularnewline
11 & -0.037936 & -0.2655 & 0.39585 \tabularnewline
12 & -0.373487 & -2.6144 & 0.005921 \tabularnewline
13 & 0.028281 & 0.198 & 0.421946 \tabularnewline
14 & 0.068483 & 0.4794 & 0.3169 \tabularnewline
15 & -0.036638 & -0.2565 & 0.399332 \tabularnewline
16 & -0.09395 & -0.6577 & 0.25692 \tabularnewline
17 & 0.049709 & 0.348 & 0.36468 \tabularnewline
18 & 0.010405 & 0.0728 & 0.471116 \tabularnewline
19 & -0.075691 & -0.5298 & 0.299308 \tabularnewline
20 & -0.132399 & -0.9268 & 0.179289 \tabularnewline
21 & 0.074088 & 0.5186 & 0.303182 \tabularnewline
22 & -0.01388 & -0.0972 & 0.461497 \tabularnewline
23 & 0.114476 & 0.8013 & 0.213405 \tabularnewline
24 & -0.181496 & -1.2705 & 0.104958 \tabularnewline
25 & 0.117881 & 0.8252 & 0.206638 \tabularnewline
26 & 0.030516 & 0.2136 & 0.415868 \tabularnewline
27 & 0.004298 & 0.0301 & 0.488061 \tabularnewline
28 & -0.086168 & -0.6032 & 0.274587 \tabularnewline
29 & -0.025154 & -0.1761 & 0.43048 \tabularnewline
30 & 0.069623 & 0.4874 & 0.314087 \tabularnewline
31 & -0.011062 & -0.0774 & 0.469296 \tabularnewline
32 & 0.071854 & 0.503 & 0.308617 \tabularnewline
33 & -0.005457 & -0.0382 & 0.484843 \tabularnewline
34 & -0.11104 & -0.7773 & 0.220365 \tabularnewline
35 & 0.00997 & 0.0698 & 0.472324 \tabularnewline
36 & -0.101377 & -0.7096 & 0.240646 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59771&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]0.337201[/C][C]2.3604[/C][C]0.01114[/C][/ROW]
[ROW][C]2[/C][C]0.289144[/C][C]2.024[/C][C]0.02422[/C][/ROW]
[ROW][C]3[/C][C]0.064561[/C][C]0.4519[/C][C]0.326658[/C][/ROW]
[ROW][C]4[/C][C]0.021018[/C][C]0.1471[/C][C]0.441818[/C][/ROW]
[ROW][C]5[/C][C]-0.138371[/C][C]-0.9686[/C][C]0.168752[/C][/ROW]
[ROW][C]6[/C][C]0.037658[/C][C]0.2636[/C][C]0.396595[/C][/ROW]
[ROW][C]7[/C][C]-0.013163[/C][C]-0.0921[/C][C]0.46348[/C][/ROW]
[ROW][C]8[/C][C]-0.03449[/C][C]-0.2414[/C][C]0.405114[/C][/ROW]
[ROW][C]9[/C][C]-0.09937[/C][C]-0.6956[/C][C]0.244986[/C][/ROW]
[ROW][C]10[/C][C]-0.1096[/C][C]-0.7672[/C][C]0.223321[/C][/ROW]
[ROW][C]11[/C][C]-0.037936[/C][C]-0.2655[/C][C]0.39585[/C][/ROW]
[ROW][C]12[/C][C]-0.373487[/C][C]-2.6144[/C][C]0.005921[/C][/ROW]
[ROW][C]13[/C][C]0.028281[/C][C]0.198[/C][C]0.421946[/C][/ROW]
[ROW][C]14[/C][C]0.068483[/C][C]0.4794[/C][C]0.3169[/C][/ROW]
[ROW][C]15[/C][C]-0.036638[/C][C]-0.2565[/C][C]0.399332[/C][/ROW]
[ROW][C]16[/C][C]-0.09395[/C][C]-0.6577[/C][C]0.25692[/C][/ROW]
[ROW][C]17[/C][C]0.049709[/C][C]0.348[/C][C]0.36468[/C][/ROW]
[ROW][C]18[/C][C]0.010405[/C][C]0.0728[/C][C]0.471116[/C][/ROW]
[ROW][C]19[/C][C]-0.075691[/C][C]-0.5298[/C][C]0.299308[/C][/ROW]
[ROW][C]20[/C][C]-0.132399[/C][C]-0.9268[/C][C]0.179289[/C][/ROW]
[ROW][C]21[/C][C]0.074088[/C][C]0.5186[/C][C]0.303182[/C][/ROW]
[ROW][C]22[/C][C]-0.01388[/C][C]-0.0972[/C][C]0.461497[/C][/ROW]
[ROW][C]23[/C][C]0.114476[/C][C]0.8013[/C][C]0.213405[/C][/ROW]
[ROW][C]24[/C][C]-0.181496[/C][C]-1.2705[/C][C]0.104958[/C][/ROW]
[ROW][C]25[/C][C]0.117881[/C][C]0.8252[/C][C]0.206638[/C][/ROW]
[ROW][C]26[/C][C]0.030516[/C][C]0.2136[/C][C]0.415868[/C][/ROW]
[ROW][C]27[/C][C]0.004298[/C][C]0.0301[/C][C]0.488061[/C][/ROW]
[ROW][C]28[/C][C]-0.086168[/C][C]-0.6032[/C][C]0.274587[/C][/ROW]
[ROW][C]29[/C][C]-0.025154[/C][C]-0.1761[/C][C]0.43048[/C][/ROW]
[ROW][C]30[/C][C]0.069623[/C][C]0.4874[/C][C]0.314087[/C][/ROW]
[ROW][C]31[/C][C]-0.011062[/C][C]-0.0774[/C][C]0.469296[/C][/ROW]
[ROW][C]32[/C][C]0.071854[/C][C]0.503[/C][C]0.308617[/C][/ROW]
[ROW][C]33[/C][C]-0.005457[/C][C]-0.0382[/C][C]0.484843[/C][/ROW]
[ROW][C]34[/C][C]-0.11104[/C][C]-0.7773[/C][C]0.220365[/C][/ROW]
[ROW][C]35[/C][C]0.00997[/C][C]0.0698[/C][C]0.472324[/C][/ROW]
[ROW][C]36[/C][C]-0.101377[/C][C]-0.7096[/C][C]0.240646[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59771&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59771&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
10.3372012.36040.01114
20.2891442.0240.02422
30.0645610.45190.326658
40.0210180.14710.441818
5-0.138371-0.96860.168752
60.0376580.26360.396595
7-0.013163-0.09210.46348
8-0.03449-0.24140.405114
9-0.09937-0.69560.244986
10-0.1096-0.76720.223321
11-0.037936-0.26550.39585
12-0.373487-2.61440.005921
130.0282810.1980.421946
140.0684830.47940.3169
15-0.036638-0.25650.399332
16-0.09395-0.65770.25692
170.0497090.3480.36468
180.0104050.07280.471116
19-0.075691-0.52980.299308
20-0.132399-0.92680.179289
210.0740880.51860.303182
22-0.01388-0.09720.461497
230.1144760.80130.213405
24-0.181496-1.27050.104958
250.1178810.82520.206638
260.0305160.21360.415868
270.0042980.03010.488061
28-0.086168-0.60320.274587
29-0.025154-0.17610.43048
300.0696230.48740.314087
31-0.011062-0.07740.469296
320.0718540.5030.308617
33-0.005457-0.03820.484843
34-0.11104-0.77730.220365
350.009970.06980.472324
36-0.101377-0.70960.240646



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