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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 computationTue, 24 Nov 2009 09:49:48 -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/24/t125908147763lfwctiala9tdt.htm/, Retrieved Sat, 25 May 2024 04:45:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59161, Retrieved Sat, 25 May 2024 04:45:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact211
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  D        [(Partial) Autocorrelation Function] [] [2009-11-24 16:19:12] [b7349fb284cae6f1172638396d27b11f]
- R P             [(Partial) Autocorrelation Function] [] [2009-11-24 16:49:48] [6dfcce621b31349cab7f0d189e6f8a9d] [Current]
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Dataseries X:
116222
110924
103753
99983
93302
91496
119321
139261
133739
123913
113438
109416
109406
105645
101328
97686
93093
91382
122257
139183
139887
131822
116805
113706
113012
110452
107005
102841
98173
98181
137277
147579
146571
138920
130340
128140
127059
122860
117702
113537
108366
111078
150739
159129
157928
147768
137507
136919
136151
133001
125554
119647
114158
116193
152803
161761
160942
149470
139208
134588
130322
126611
122401
117352
112135
112879
148729
157230
157221
146681
136524
132111




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=59161&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=59161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59161&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8839386.8470
20.7835036.0690
30.7195775.57380
40.6801465.26841e-06
50.6370024.93423e-06
60.5718514.42952e-05
70.5074043.93030.000111
80.4079443.15990.001236
90.3544142.74530.003983
100.2850052.20760.015552
110.1825161.41380.0813
120.1139810.88290.190409
130.0503880.39030.348847
140.0038160.02960.48826
15-0.081568-0.63180.264952
16-0.164798-1.27650.103345
17-0.253852-1.96630.026946
18-0.324682-2.5150.007301
19-0.333596-2.5840.006109
20-0.370451-2.86950.002835
21-0.409137-3.16920.001203
22-0.461267-3.5730.000352
23-0.48033-3.72060.00022
24-0.503006-3.89630.000124
25-0.510137-3.95150.000104
26-0.497172-3.85110.000144
27-0.479026-3.71050.000227
28-0.455573-3.52890.000404
29-0.461364-3.57370.000351
30-0.449062-3.47840.000473
31-0.409352-3.17080.001197
32-0.363908-2.81880.00326
33-0.324201-2.51130.007371
34-0.295326-2.28760.012851
35-0.265101-2.05350.022197
36-0.22894-1.77340.040622

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.883938 & 6.847 & 0 \tabularnewline
2 & 0.783503 & 6.069 & 0 \tabularnewline
3 & 0.719577 & 5.5738 & 0 \tabularnewline
4 & 0.680146 & 5.2684 & 1e-06 \tabularnewline
5 & 0.637002 & 4.9342 & 3e-06 \tabularnewline
6 & 0.571851 & 4.4295 & 2e-05 \tabularnewline
7 & 0.507404 & 3.9303 & 0.000111 \tabularnewline
8 & 0.407944 & 3.1599 & 0.001236 \tabularnewline
9 & 0.354414 & 2.7453 & 0.003983 \tabularnewline
10 & 0.285005 & 2.2076 & 0.015552 \tabularnewline
11 & 0.182516 & 1.4138 & 0.0813 \tabularnewline
12 & 0.113981 & 0.8829 & 0.190409 \tabularnewline
13 & 0.050388 & 0.3903 & 0.348847 \tabularnewline
14 & 0.003816 & 0.0296 & 0.48826 \tabularnewline
15 & -0.081568 & -0.6318 & 0.264952 \tabularnewline
16 & -0.164798 & -1.2765 & 0.103345 \tabularnewline
17 & -0.253852 & -1.9663 & 0.026946 \tabularnewline
18 & -0.324682 & -2.515 & 0.007301 \tabularnewline
19 & -0.333596 & -2.584 & 0.006109 \tabularnewline
20 & -0.370451 & -2.8695 & 0.002835 \tabularnewline
21 & -0.409137 & -3.1692 & 0.001203 \tabularnewline
22 & -0.461267 & -3.573 & 0.000352 \tabularnewline
23 & -0.48033 & -3.7206 & 0.00022 \tabularnewline
24 & -0.503006 & -3.8963 & 0.000124 \tabularnewline
25 & -0.510137 & -3.9515 & 0.000104 \tabularnewline
26 & -0.497172 & -3.8511 & 0.000144 \tabularnewline
27 & -0.479026 & -3.7105 & 0.000227 \tabularnewline
28 & -0.455573 & -3.5289 & 0.000404 \tabularnewline
29 & -0.461364 & -3.5737 & 0.000351 \tabularnewline
30 & -0.449062 & -3.4784 & 0.000473 \tabularnewline
31 & -0.409352 & -3.1708 & 0.001197 \tabularnewline
32 & -0.363908 & -2.8188 & 0.00326 \tabularnewline
33 & -0.324201 & -2.5113 & 0.007371 \tabularnewline
34 & -0.295326 & -2.2876 & 0.012851 \tabularnewline
35 & -0.265101 & -2.0535 & 0.022197 \tabularnewline
36 & -0.22894 & -1.7734 & 0.040622 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59161&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]0.883938[/C][C]6.847[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.783503[/C][C]6.069[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.719577[/C][C]5.5738[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.680146[/C][C]5.2684[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.637002[/C][C]4.9342[/C][C]3e-06[/C][/ROW]
[ROW][C]6[/C][C]0.571851[/C][C]4.4295[/C][C]2e-05[/C][/ROW]
[ROW][C]7[/C][C]0.507404[/C][C]3.9303[/C][C]0.000111[/C][/ROW]
[ROW][C]8[/C][C]0.407944[/C][C]3.1599[/C][C]0.001236[/C][/ROW]
[ROW][C]9[/C][C]0.354414[/C][C]2.7453[/C][C]0.003983[/C][/ROW]
[ROW][C]10[/C][C]0.285005[/C][C]2.2076[/C][C]0.015552[/C][/ROW]
[ROW][C]11[/C][C]0.182516[/C][C]1.4138[/C][C]0.0813[/C][/ROW]
[ROW][C]12[/C][C]0.113981[/C][C]0.8829[/C][C]0.190409[/C][/ROW]
[ROW][C]13[/C][C]0.050388[/C][C]0.3903[/C][C]0.348847[/C][/ROW]
[ROW][C]14[/C][C]0.003816[/C][C]0.0296[/C][C]0.48826[/C][/ROW]
[ROW][C]15[/C][C]-0.081568[/C][C]-0.6318[/C][C]0.264952[/C][/ROW]
[ROW][C]16[/C][C]-0.164798[/C][C]-1.2765[/C][C]0.103345[/C][/ROW]
[ROW][C]17[/C][C]-0.253852[/C][C]-1.9663[/C][C]0.026946[/C][/ROW]
[ROW][C]18[/C][C]-0.324682[/C][C]-2.515[/C][C]0.007301[/C][/ROW]
[ROW][C]19[/C][C]-0.333596[/C][C]-2.584[/C][C]0.006109[/C][/ROW]
[ROW][C]20[/C][C]-0.370451[/C][C]-2.8695[/C][C]0.002835[/C][/ROW]
[ROW][C]21[/C][C]-0.409137[/C][C]-3.1692[/C][C]0.001203[/C][/ROW]
[ROW][C]22[/C][C]-0.461267[/C][C]-3.573[/C][C]0.000352[/C][/ROW]
[ROW][C]23[/C][C]-0.48033[/C][C]-3.7206[/C][C]0.00022[/C][/ROW]
[ROW][C]24[/C][C]-0.503006[/C][C]-3.8963[/C][C]0.000124[/C][/ROW]
[ROW][C]25[/C][C]-0.510137[/C][C]-3.9515[/C][C]0.000104[/C][/ROW]
[ROW][C]26[/C][C]-0.497172[/C][C]-3.8511[/C][C]0.000144[/C][/ROW]
[ROW][C]27[/C][C]-0.479026[/C][C]-3.7105[/C][C]0.000227[/C][/ROW]
[ROW][C]28[/C][C]-0.455573[/C][C]-3.5289[/C][C]0.000404[/C][/ROW]
[ROW][C]29[/C][C]-0.461364[/C][C]-3.5737[/C][C]0.000351[/C][/ROW]
[ROW][C]30[/C][C]-0.449062[/C][C]-3.4784[/C][C]0.000473[/C][/ROW]
[ROW][C]31[/C][C]-0.409352[/C][C]-3.1708[/C][C]0.001197[/C][/ROW]
[ROW][C]32[/C][C]-0.363908[/C][C]-2.8188[/C][C]0.00326[/C][/ROW]
[ROW][C]33[/C][C]-0.324201[/C][C]-2.5113[/C][C]0.007371[/C][/ROW]
[ROW][C]34[/C][C]-0.295326[/C][C]-2.2876[/C][C]0.012851[/C][/ROW]
[ROW][C]35[/C][C]-0.265101[/C][C]-2.0535[/C][C]0.022197[/C][/ROW]
[ROW][C]36[/C][C]-0.22894[/C][C]-1.7734[/C][C]0.040622[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59161&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
10.8839386.8470
20.7835036.0690
30.7195775.57380
40.6801465.26841e-06
50.6370024.93423e-06
60.5718514.42952e-05
70.5074043.93030.000111
80.4079443.15990.001236
90.3544142.74530.003983
100.2850052.20760.015552
110.1825161.41380.0813
120.1139810.88290.190409
130.0503880.39030.348847
140.0038160.02960.48826
15-0.081568-0.63180.264952
16-0.164798-1.27650.103345
17-0.253852-1.96630.026946
18-0.324682-2.5150.007301
19-0.333596-2.5840.006109
20-0.370451-2.86950.002835
21-0.409137-3.16920.001203
22-0.461267-3.5730.000352
23-0.48033-3.72060.00022
24-0.503006-3.89630.000124
25-0.510137-3.95150.000104
26-0.497172-3.85110.000144
27-0.479026-3.71050.000227
28-0.455573-3.52890.000404
29-0.461364-3.57370.000351
30-0.449062-3.47840.000473
31-0.409352-3.17080.001197
32-0.363908-2.81880.00326
33-0.324201-2.51130.007371
34-0.295326-2.28760.012851
35-0.265101-2.05350.022197
36-0.22894-1.77340.040622







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8839386.8470
20.0098640.07640.469676
30.1149020.890.188503
40.0958170.74220.230432
5-0.000494-0.00380.498479
6-0.091446-0.70830.240738
7-0.033482-0.25940.398126
8-0.230502-1.78550.03962
90.110580.85650.197551
10-0.156011-1.20850.115806
11-0.203194-1.57390.060381
120.0878830.68070.249327
13-0.067238-0.52080.302203
140.0123030.09530.462196
15-0.15629-1.21060.115394
16-0.112422-0.87080.193662
17-0.113519-0.87930.191369
18-0.038032-0.29460.384661
190.1209880.93720.176214
20-0.073639-0.57040.285267
21-0.009644-0.07470.47035
22-0.074965-0.58070.281818
230.0291710.2260.411001
24-0.106022-0.82120.20738
250.0715020.55390.290869
26-0.023406-0.18130.42837
270.126660.98110.165241
28-0.078259-0.60620.273337
29-0.160367-1.24220.109499
300.0738740.57220.284653
310.0964240.74690.229021
32-0.012975-0.10050.460141
33-0.096786-0.74970.228183
34-0.013365-0.10350.458946
35-0.089777-0.69540.244742
360.0803620.62250.267991

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.883938 & 6.847 & 0 \tabularnewline
2 & 0.009864 & 0.0764 & 0.469676 \tabularnewline
3 & 0.114902 & 0.89 & 0.188503 \tabularnewline
4 & 0.095817 & 0.7422 & 0.230432 \tabularnewline
5 & -0.000494 & -0.0038 & 0.498479 \tabularnewline
6 & -0.091446 & -0.7083 & 0.240738 \tabularnewline
7 & -0.033482 & -0.2594 & 0.398126 \tabularnewline
8 & -0.230502 & -1.7855 & 0.03962 \tabularnewline
9 & 0.11058 & 0.8565 & 0.197551 \tabularnewline
10 & -0.156011 & -1.2085 & 0.115806 \tabularnewline
11 & -0.203194 & -1.5739 & 0.060381 \tabularnewline
12 & 0.087883 & 0.6807 & 0.249327 \tabularnewline
13 & -0.067238 & -0.5208 & 0.302203 \tabularnewline
14 & 0.012303 & 0.0953 & 0.462196 \tabularnewline
15 & -0.15629 & -1.2106 & 0.115394 \tabularnewline
16 & -0.112422 & -0.8708 & 0.193662 \tabularnewline
17 & -0.113519 & -0.8793 & 0.191369 \tabularnewline
18 & -0.038032 & -0.2946 & 0.384661 \tabularnewline
19 & 0.120988 & 0.9372 & 0.176214 \tabularnewline
20 & -0.073639 & -0.5704 & 0.285267 \tabularnewline
21 & -0.009644 & -0.0747 & 0.47035 \tabularnewline
22 & -0.074965 & -0.5807 & 0.281818 \tabularnewline
23 & 0.029171 & 0.226 & 0.411001 \tabularnewline
24 & -0.106022 & -0.8212 & 0.20738 \tabularnewline
25 & 0.071502 & 0.5539 & 0.290869 \tabularnewline
26 & -0.023406 & -0.1813 & 0.42837 \tabularnewline
27 & 0.12666 & 0.9811 & 0.165241 \tabularnewline
28 & -0.078259 & -0.6062 & 0.273337 \tabularnewline
29 & -0.160367 & -1.2422 & 0.109499 \tabularnewline
30 & 0.073874 & 0.5722 & 0.284653 \tabularnewline
31 & 0.096424 & 0.7469 & 0.229021 \tabularnewline
32 & -0.012975 & -0.1005 & 0.460141 \tabularnewline
33 & -0.096786 & -0.7497 & 0.228183 \tabularnewline
34 & -0.013365 & -0.1035 & 0.458946 \tabularnewline
35 & -0.089777 & -0.6954 & 0.244742 \tabularnewline
36 & 0.080362 & 0.6225 & 0.267991 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59161&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]0.883938[/C][C]6.847[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.009864[/C][C]0.0764[/C][C]0.469676[/C][/ROW]
[ROW][C]3[/C][C]0.114902[/C][C]0.89[/C][C]0.188503[/C][/ROW]
[ROW][C]4[/C][C]0.095817[/C][C]0.7422[/C][C]0.230432[/C][/ROW]
[ROW][C]5[/C][C]-0.000494[/C][C]-0.0038[/C][C]0.498479[/C][/ROW]
[ROW][C]6[/C][C]-0.091446[/C][C]-0.7083[/C][C]0.240738[/C][/ROW]
[ROW][C]7[/C][C]-0.033482[/C][C]-0.2594[/C][C]0.398126[/C][/ROW]
[ROW][C]8[/C][C]-0.230502[/C][C]-1.7855[/C][C]0.03962[/C][/ROW]
[ROW][C]9[/C][C]0.11058[/C][C]0.8565[/C][C]0.197551[/C][/ROW]
[ROW][C]10[/C][C]-0.156011[/C][C]-1.2085[/C][C]0.115806[/C][/ROW]
[ROW][C]11[/C][C]-0.203194[/C][C]-1.5739[/C][C]0.060381[/C][/ROW]
[ROW][C]12[/C][C]0.087883[/C][C]0.6807[/C][C]0.249327[/C][/ROW]
[ROW][C]13[/C][C]-0.067238[/C][C]-0.5208[/C][C]0.302203[/C][/ROW]
[ROW][C]14[/C][C]0.012303[/C][C]0.0953[/C][C]0.462196[/C][/ROW]
[ROW][C]15[/C][C]-0.15629[/C][C]-1.2106[/C][C]0.115394[/C][/ROW]
[ROW][C]16[/C][C]-0.112422[/C][C]-0.8708[/C][C]0.193662[/C][/ROW]
[ROW][C]17[/C][C]-0.113519[/C][C]-0.8793[/C][C]0.191369[/C][/ROW]
[ROW][C]18[/C][C]-0.038032[/C][C]-0.2946[/C][C]0.384661[/C][/ROW]
[ROW][C]19[/C][C]0.120988[/C][C]0.9372[/C][C]0.176214[/C][/ROW]
[ROW][C]20[/C][C]-0.073639[/C][C]-0.5704[/C][C]0.285267[/C][/ROW]
[ROW][C]21[/C][C]-0.009644[/C][C]-0.0747[/C][C]0.47035[/C][/ROW]
[ROW][C]22[/C][C]-0.074965[/C][C]-0.5807[/C][C]0.281818[/C][/ROW]
[ROW][C]23[/C][C]0.029171[/C][C]0.226[/C][C]0.411001[/C][/ROW]
[ROW][C]24[/C][C]-0.106022[/C][C]-0.8212[/C][C]0.20738[/C][/ROW]
[ROW][C]25[/C][C]0.071502[/C][C]0.5539[/C][C]0.290869[/C][/ROW]
[ROW][C]26[/C][C]-0.023406[/C][C]-0.1813[/C][C]0.42837[/C][/ROW]
[ROW][C]27[/C][C]0.12666[/C][C]0.9811[/C][C]0.165241[/C][/ROW]
[ROW][C]28[/C][C]-0.078259[/C][C]-0.6062[/C][C]0.273337[/C][/ROW]
[ROW][C]29[/C][C]-0.160367[/C][C]-1.2422[/C][C]0.109499[/C][/ROW]
[ROW][C]30[/C][C]0.073874[/C][C]0.5722[/C][C]0.284653[/C][/ROW]
[ROW][C]31[/C][C]0.096424[/C][C]0.7469[/C][C]0.229021[/C][/ROW]
[ROW][C]32[/C][C]-0.012975[/C][C]-0.1005[/C][C]0.460141[/C][/ROW]
[ROW][C]33[/C][C]-0.096786[/C][C]-0.7497[/C][C]0.228183[/C][/ROW]
[ROW][C]34[/C][C]-0.013365[/C][C]-0.1035[/C][C]0.458946[/C][/ROW]
[ROW][C]35[/C][C]-0.089777[/C][C]-0.6954[/C][C]0.244742[/C][/ROW]
[ROW][C]36[/C][C]0.080362[/C][C]0.6225[/C][C]0.267991[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59161&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59161&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
10.8839386.8470
20.0098640.07640.469676
30.1149020.890.188503
40.0958170.74220.230432
5-0.000494-0.00380.498479
6-0.091446-0.70830.240738
7-0.033482-0.25940.398126
8-0.230502-1.78550.03962
90.110580.85650.197551
10-0.156011-1.20850.115806
11-0.203194-1.57390.060381
120.0878830.68070.249327
13-0.067238-0.52080.302203
140.0123030.09530.462196
15-0.15629-1.21060.115394
16-0.112422-0.87080.193662
17-0.113519-0.87930.191369
18-0.038032-0.29460.384661
190.1209880.93720.176214
20-0.073639-0.57040.285267
21-0.009644-0.07470.47035
22-0.074965-0.58070.281818
230.0291710.2260.411001
24-0.106022-0.82120.20738
250.0715020.55390.290869
26-0.023406-0.18130.42837
270.126660.98110.165241
28-0.078259-0.60620.273337
29-0.160367-1.24220.109499
300.0738740.57220.284653
310.0964240.74690.229021
32-0.012975-0.10050.460141
33-0.096786-0.74970.228183
34-0.013365-0.10350.458946
35-0.089777-0.69540.244742
360.0803620.62250.267991



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')