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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, 10 Dec 2009 12:05:07 -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/10/t12604721113zr6v55dacajgan.htm/, Retrieved Thu, 28 Mar 2024 22:57:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65735, Retrieved Thu, 28 Mar 2024 22:57:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
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 14:48:46] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [WS 9] [2009-12-02 18:29:08] [3e19a07d230ba260a720e0e03e0f40f2]
-    D      [(Partial) Autocorrelation Function] [Workshop 9] [2009-12-04 19:44:00] [786e067c4f7cec17385c4742b96b6dfa]
-   P           [(Partial) Autocorrelation Function] [WS 9 verbetering d=2] [2009-12-10 19:05:07] [b653746fe14da1ddc21bd75262e8c46b] [Current]
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Dataseries X:
126.51
131.02
136.51
138.04
132.92
129.61
122.96
124.04
121.29
124.56
118.53
113.14
114.15
122.17
129.23
131.19
129.12
128.28
126.83
138.13
140.52
146.83
135.14
131.84
125.7
128.98
133.25
136.76
133.24
128.54
121.08
120.23
119.08
125.75
126.89
126.6
121.89
123.44
126.46
129.49
127.78
125.29
119.02
119.96
122.86
131.89
132.73
135.01
136.71
142.73
144.43
144.93
138.75
130.22
122.19
128.4
140.43
153.5
149.33
142.97




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=65735&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=65735&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65735&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
1-0.063126-0.42810.335274
20.041760.28320.389135
3-0.464993-3.15370.001419
4-0.059081-0.40070.345246
5-0.160609-1.08930.140846
60.0234530.15910.437157
70.3195672.16740.017708
80.0235610.15980.436869
90.0872860.5920.278373
10-0.217694-1.47650.073316
110.1251490.84880.200194
12-0.303658-2.05950.022565
130.0685460.46490.322098
140.0618150.41920.338494
150.2374031.61010.057104
16-0.006448-0.04370.482655
17-0.066124-0.44850.327957
18-0.121954-0.82710.206216
19-0.181689-1.23230.112054
20-0.049667-0.33690.368878
210.1818531.23340.111848
220.2307811.56520.062192
230.0320220.21720.414512
24-0.1189-0.80640.212075
25-0.140416-0.95230.172949
26-0.108803-0.73790.232151
27-0.04322-0.29310.38537
280.1271990.86270.196387
290.1307510.88680.1899
300.0209050.14180.443935
31-0.061649-0.41810.338901
32-0.060575-0.41080.341549
33-0.040703-0.27610.391868
34-0.069983-0.47460.318642
35-0.016205-0.10990.456481
360.0915190.62070.268927

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.063126 & -0.4281 & 0.335274 \tabularnewline
2 & 0.04176 & 0.2832 & 0.389135 \tabularnewline
3 & -0.464993 & -3.1537 & 0.001419 \tabularnewline
4 & -0.059081 & -0.4007 & 0.345246 \tabularnewline
5 & -0.160609 & -1.0893 & 0.140846 \tabularnewline
6 & 0.023453 & 0.1591 & 0.437157 \tabularnewline
7 & 0.319567 & 2.1674 & 0.017708 \tabularnewline
8 & 0.023561 & 0.1598 & 0.436869 \tabularnewline
9 & 0.087286 & 0.592 & 0.278373 \tabularnewline
10 & -0.217694 & -1.4765 & 0.073316 \tabularnewline
11 & 0.125149 & 0.8488 & 0.200194 \tabularnewline
12 & -0.303658 & -2.0595 & 0.022565 \tabularnewline
13 & 0.068546 & 0.4649 & 0.322098 \tabularnewline
14 & 0.061815 & 0.4192 & 0.338494 \tabularnewline
15 & 0.237403 & 1.6101 & 0.057104 \tabularnewline
16 & -0.006448 & -0.0437 & 0.482655 \tabularnewline
17 & -0.066124 & -0.4485 & 0.327957 \tabularnewline
18 & -0.121954 & -0.8271 & 0.206216 \tabularnewline
19 & -0.181689 & -1.2323 & 0.112054 \tabularnewline
20 & -0.049667 & -0.3369 & 0.368878 \tabularnewline
21 & 0.181853 & 1.2334 & 0.111848 \tabularnewline
22 & 0.230781 & 1.5652 & 0.062192 \tabularnewline
23 & 0.032022 & 0.2172 & 0.414512 \tabularnewline
24 & -0.1189 & -0.8064 & 0.212075 \tabularnewline
25 & -0.140416 & -0.9523 & 0.172949 \tabularnewline
26 & -0.108803 & -0.7379 & 0.232151 \tabularnewline
27 & -0.04322 & -0.2931 & 0.38537 \tabularnewline
28 & 0.127199 & 0.8627 & 0.196387 \tabularnewline
29 & 0.130751 & 0.8868 & 0.1899 \tabularnewline
30 & 0.020905 & 0.1418 & 0.443935 \tabularnewline
31 & -0.061649 & -0.4181 & 0.338901 \tabularnewline
32 & -0.060575 & -0.4108 & 0.341549 \tabularnewline
33 & -0.040703 & -0.2761 & 0.391868 \tabularnewline
34 & -0.069983 & -0.4746 & 0.318642 \tabularnewline
35 & -0.016205 & -0.1099 & 0.456481 \tabularnewline
36 & 0.091519 & 0.6207 & 0.268927 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65735&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]-0.063126[/C][C]-0.4281[/C][C]0.335274[/C][/ROW]
[ROW][C]2[/C][C]0.04176[/C][C]0.2832[/C][C]0.389135[/C][/ROW]
[ROW][C]3[/C][C]-0.464993[/C][C]-3.1537[/C][C]0.001419[/C][/ROW]
[ROW][C]4[/C][C]-0.059081[/C][C]-0.4007[/C][C]0.345246[/C][/ROW]
[ROW][C]5[/C][C]-0.160609[/C][C]-1.0893[/C][C]0.140846[/C][/ROW]
[ROW][C]6[/C][C]0.023453[/C][C]0.1591[/C][C]0.437157[/C][/ROW]
[ROW][C]7[/C][C]0.319567[/C][C]2.1674[/C][C]0.017708[/C][/ROW]
[ROW][C]8[/C][C]0.023561[/C][C]0.1598[/C][C]0.436869[/C][/ROW]
[ROW][C]9[/C][C]0.087286[/C][C]0.592[/C][C]0.278373[/C][/ROW]
[ROW][C]10[/C][C]-0.217694[/C][C]-1.4765[/C][C]0.073316[/C][/ROW]
[ROW][C]11[/C][C]0.125149[/C][C]0.8488[/C][C]0.200194[/C][/ROW]
[ROW][C]12[/C][C]-0.303658[/C][C]-2.0595[/C][C]0.022565[/C][/ROW]
[ROW][C]13[/C][C]0.068546[/C][C]0.4649[/C][C]0.322098[/C][/ROW]
[ROW][C]14[/C][C]0.061815[/C][C]0.4192[/C][C]0.338494[/C][/ROW]
[ROW][C]15[/C][C]0.237403[/C][C]1.6101[/C][C]0.057104[/C][/ROW]
[ROW][C]16[/C][C]-0.006448[/C][C]-0.0437[/C][C]0.482655[/C][/ROW]
[ROW][C]17[/C][C]-0.066124[/C][C]-0.4485[/C][C]0.327957[/C][/ROW]
[ROW][C]18[/C][C]-0.121954[/C][C]-0.8271[/C][C]0.206216[/C][/ROW]
[ROW][C]19[/C][C]-0.181689[/C][C]-1.2323[/C][C]0.112054[/C][/ROW]
[ROW][C]20[/C][C]-0.049667[/C][C]-0.3369[/C][C]0.368878[/C][/ROW]
[ROW][C]21[/C][C]0.181853[/C][C]1.2334[/C][C]0.111848[/C][/ROW]
[ROW][C]22[/C][C]0.230781[/C][C]1.5652[/C][C]0.062192[/C][/ROW]
[ROW][C]23[/C][C]0.032022[/C][C]0.2172[/C][C]0.414512[/C][/ROW]
[ROW][C]24[/C][C]-0.1189[/C][C]-0.8064[/C][C]0.212075[/C][/ROW]
[ROW][C]25[/C][C]-0.140416[/C][C]-0.9523[/C][C]0.172949[/C][/ROW]
[ROW][C]26[/C][C]-0.108803[/C][C]-0.7379[/C][C]0.232151[/C][/ROW]
[ROW][C]27[/C][C]-0.04322[/C][C]-0.2931[/C][C]0.38537[/C][/ROW]
[ROW][C]28[/C][C]0.127199[/C][C]0.8627[/C][C]0.196387[/C][/ROW]
[ROW][C]29[/C][C]0.130751[/C][C]0.8868[/C][C]0.1899[/C][/ROW]
[ROW][C]30[/C][C]0.020905[/C][C]0.1418[/C][C]0.443935[/C][/ROW]
[ROW][C]31[/C][C]-0.061649[/C][C]-0.4181[/C][C]0.338901[/C][/ROW]
[ROW][C]32[/C][C]-0.060575[/C][C]-0.4108[/C][C]0.341549[/C][/ROW]
[ROW][C]33[/C][C]-0.040703[/C][C]-0.2761[/C][C]0.391868[/C][/ROW]
[ROW][C]34[/C][C]-0.069983[/C][C]-0.4746[/C][C]0.318642[/C][/ROW]
[ROW][C]35[/C][C]-0.016205[/C][C]-0.1099[/C][C]0.456481[/C][/ROW]
[ROW][C]36[/C][C]0.091519[/C][C]0.6207[/C][C]0.268927[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65735&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65735&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
1-0.063126-0.42810.335274
20.041760.28320.389135
3-0.464993-3.15370.001419
4-0.059081-0.40070.345246
5-0.160609-1.08930.140846
60.0234530.15910.437157
70.3195672.16740.017708
80.0235610.15980.436869
90.0872860.5920.278373
10-0.217694-1.47650.073316
110.1251490.84880.200194
12-0.303658-2.05950.022565
130.0685460.46490.322098
140.0618150.41920.338494
150.2374031.61010.057104
16-0.006448-0.04370.482655
17-0.066124-0.44850.327957
18-0.121954-0.82710.206216
19-0.181689-1.23230.112054
20-0.049667-0.33690.368878
210.1818531.23340.111848
220.2307811.56520.062192
230.0320220.21720.414512
24-0.1189-0.80640.212075
25-0.140416-0.95230.172949
26-0.108803-0.73790.232151
27-0.04322-0.29310.38537
280.1271990.86270.196387
290.1307510.88680.1899
300.0209050.14180.443935
31-0.061649-0.41810.338901
32-0.060575-0.41080.341549
33-0.040703-0.27610.391868
34-0.069983-0.47460.318642
35-0.016205-0.10990.456481
360.0915190.62070.268927







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.063126-0.42810.335274
20.0379260.25720.399075
3-0.462568-3.13730.001486
4-0.139137-0.94370.175133
5-0.196925-1.33560.094124
6-0.306153-2.07640.021734
70.257231.74460.043865
8-0.156742-1.06310.146648
9-0.047097-0.31940.375424
100.0568190.38540.35087
110.0798120.54130.295452
12-0.243674-1.65270.052604
130.0157530.10680.45769
140.1363540.92480.179949
15-0.006244-0.04230.483202
160.0503480.34150.367149
170.060730.41190.341167
18-0.206044-1.39750.08449
19-0.027179-0.18430.42728
20-0.098791-0.670.253094
210.0722190.48980.313297
220.0347550.23570.407349
230.0149150.10120.459933
24-0.108269-0.73430.233241
25-0.057356-0.3890.349532
26-0.024356-0.16520.434759
27-0.04526-0.3070.380126
28-0.010402-0.07050.472031
290.009030.06120.475714
30-0.162808-1.10420.137621
310.0134540.09130.463845
32-0.103708-0.70340.242682
330.007120.04830.480847
34-0.027959-0.18960.425217
35-0.14992-1.01680.157282
36-0.061837-0.41940.33844

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.063126 & -0.4281 & 0.335274 \tabularnewline
2 & 0.037926 & 0.2572 & 0.399075 \tabularnewline
3 & -0.462568 & -3.1373 & 0.001486 \tabularnewline
4 & -0.139137 & -0.9437 & 0.175133 \tabularnewline
5 & -0.196925 & -1.3356 & 0.094124 \tabularnewline
6 & -0.306153 & -2.0764 & 0.021734 \tabularnewline
7 & 0.25723 & 1.7446 & 0.043865 \tabularnewline
8 & -0.156742 & -1.0631 & 0.146648 \tabularnewline
9 & -0.047097 & -0.3194 & 0.375424 \tabularnewline
10 & 0.056819 & 0.3854 & 0.35087 \tabularnewline
11 & 0.079812 & 0.5413 & 0.295452 \tabularnewline
12 & -0.243674 & -1.6527 & 0.052604 \tabularnewline
13 & 0.015753 & 0.1068 & 0.45769 \tabularnewline
14 & 0.136354 & 0.9248 & 0.179949 \tabularnewline
15 & -0.006244 & -0.0423 & 0.483202 \tabularnewline
16 & 0.050348 & 0.3415 & 0.367149 \tabularnewline
17 & 0.06073 & 0.4119 & 0.341167 \tabularnewline
18 & -0.206044 & -1.3975 & 0.08449 \tabularnewline
19 & -0.027179 & -0.1843 & 0.42728 \tabularnewline
20 & -0.098791 & -0.67 & 0.253094 \tabularnewline
21 & 0.072219 & 0.4898 & 0.313297 \tabularnewline
22 & 0.034755 & 0.2357 & 0.407349 \tabularnewline
23 & 0.014915 & 0.1012 & 0.459933 \tabularnewline
24 & -0.108269 & -0.7343 & 0.233241 \tabularnewline
25 & -0.057356 & -0.389 & 0.349532 \tabularnewline
26 & -0.024356 & -0.1652 & 0.434759 \tabularnewline
27 & -0.04526 & -0.307 & 0.380126 \tabularnewline
28 & -0.010402 & -0.0705 & 0.472031 \tabularnewline
29 & 0.00903 & 0.0612 & 0.475714 \tabularnewline
30 & -0.162808 & -1.1042 & 0.137621 \tabularnewline
31 & 0.013454 & 0.0913 & 0.463845 \tabularnewline
32 & -0.103708 & -0.7034 & 0.242682 \tabularnewline
33 & 0.00712 & 0.0483 & 0.480847 \tabularnewline
34 & -0.027959 & -0.1896 & 0.425217 \tabularnewline
35 & -0.14992 & -1.0168 & 0.157282 \tabularnewline
36 & -0.061837 & -0.4194 & 0.33844 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65735&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]-0.063126[/C][C]-0.4281[/C][C]0.335274[/C][/ROW]
[ROW][C]2[/C][C]0.037926[/C][C]0.2572[/C][C]0.399075[/C][/ROW]
[ROW][C]3[/C][C]-0.462568[/C][C]-3.1373[/C][C]0.001486[/C][/ROW]
[ROW][C]4[/C][C]-0.139137[/C][C]-0.9437[/C][C]0.175133[/C][/ROW]
[ROW][C]5[/C][C]-0.196925[/C][C]-1.3356[/C][C]0.094124[/C][/ROW]
[ROW][C]6[/C][C]-0.306153[/C][C]-2.0764[/C][C]0.021734[/C][/ROW]
[ROW][C]7[/C][C]0.25723[/C][C]1.7446[/C][C]0.043865[/C][/ROW]
[ROW][C]8[/C][C]-0.156742[/C][C]-1.0631[/C][C]0.146648[/C][/ROW]
[ROW][C]9[/C][C]-0.047097[/C][C]-0.3194[/C][C]0.375424[/C][/ROW]
[ROW][C]10[/C][C]0.056819[/C][C]0.3854[/C][C]0.35087[/C][/ROW]
[ROW][C]11[/C][C]0.079812[/C][C]0.5413[/C][C]0.295452[/C][/ROW]
[ROW][C]12[/C][C]-0.243674[/C][C]-1.6527[/C][C]0.052604[/C][/ROW]
[ROW][C]13[/C][C]0.015753[/C][C]0.1068[/C][C]0.45769[/C][/ROW]
[ROW][C]14[/C][C]0.136354[/C][C]0.9248[/C][C]0.179949[/C][/ROW]
[ROW][C]15[/C][C]-0.006244[/C][C]-0.0423[/C][C]0.483202[/C][/ROW]
[ROW][C]16[/C][C]0.050348[/C][C]0.3415[/C][C]0.367149[/C][/ROW]
[ROW][C]17[/C][C]0.06073[/C][C]0.4119[/C][C]0.341167[/C][/ROW]
[ROW][C]18[/C][C]-0.206044[/C][C]-1.3975[/C][C]0.08449[/C][/ROW]
[ROW][C]19[/C][C]-0.027179[/C][C]-0.1843[/C][C]0.42728[/C][/ROW]
[ROW][C]20[/C][C]-0.098791[/C][C]-0.67[/C][C]0.253094[/C][/ROW]
[ROW][C]21[/C][C]0.072219[/C][C]0.4898[/C][C]0.313297[/C][/ROW]
[ROW][C]22[/C][C]0.034755[/C][C]0.2357[/C][C]0.407349[/C][/ROW]
[ROW][C]23[/C][C]0.014915[/C][C]0.1012[/C][C]0.459933[/C][/ROW]
[ROW][C]24[/C][C]-0.108269[/C][C]-0.7343[/C][C]0.233241[/C][/ROW]
[ROW][C]25[/C][C]-0.057356[/C][C]-0.389[/C][C]0.349532[/C][/ROW]
[ROW][C]26[/C][C]-0.024356[/C][C]-0.1652[/C][C]0.434759[/C][/ROW]
[ROW][C]27[/C][C]-0.04526[/C][C]-0.307[/C][C]0.380126[/C][/ROW]
[ROW][C]28[/C][C]-0.010402[/C][C]-0.0705[/C][C]0.472031[/C][/ROW]
[ROW][C]29[/C][C]0.00903[/C][C]0.0612[/C][C]0.475714[/C][/ROW]
[ROW][C]30[/C][C]-0.162808[/C][C]-1.1042[/C][C]0.137621[/C][/ROW]
[ROW][C]31[/C][C]0.013454[/C][C]0.0913[/C][C]0.463845[/C][/ROW]
[ROW][C]32[/C][C]-0.103708[/C][C]-0.7034[/C][C]0.242682[/C][/ROW]
[ROW][C]33[/C][C]0.00712[/C][C]0.0483[/C][C]0.480847[/C][/ROW]
[ROW][C]34[/C][C]-0.027959[/C][C]-0.1896[/C][C]0.425217[/C][/ROW]
[ROW][C]35[/C][C]-0.14992[/C][C]-1.0168[/C][C]0.157282[/C][/ROW]
[ROW][C]36[/C][C]-0.061837[/C][C]-0.4194[/C][C]0.33844[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65735&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65735&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
1-0.063126-0.42810.335274
20.0379260.25720.399075
3-0.462568-3.13730.001486
4-0.139137-0.94370.175133
5-0.196925-1.33560.094124
6-0.306153-2.07640.021734
70.257231.74460.043865
8-0.156742-1.06310.146648
9-0.047097-0.31940.375424
100.0568190.38540.35087
110.0798120.54130.295452
12-0.243674-1.65270.052604
130.0157530.10680.45769
140.1363540.92480.179949
15-0.006244-0.04230.483202
160.0503480.34150.367149
170.060730.41190.341167
18-0.206044-1.39750.08449
19-0.027179-0.18430.42728
20-0.098791-0.670.253094
210.0722190.48980.313297
220.0347550.23570.407349
230.0149150.10120.459933
24-0.108269-0.73430.233241
25-0.057356-0.3890.349532
26-0.024356-0.16520.434759
27-0.04526-0.3070.380126
28-0.010402-0.07050.472031
290.009030.06120.475714
30-0.162808-1.10420.137621
310.0134540.09130.463845
32-0.103708-0.70340.242682
330.007120.04830.480847
34-0.027959-0.18960.425217
35-0.14992-1.01680.157282
36-0.061837-0.41940.33844



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')