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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 computationFri, 27 Nov 2009 14:07:22 -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/27/t1259356092sl45rmrpxwzevmg.htm/, Retrieved Fri, 05 Jun 2026 23:13:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61278, Retrieved Fri, 05 Jun 2026 23:13:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact422

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Workshop 8] [2009-11-27 14:36:34] [786e067c4f7cec17385c4742b96b6dfa]
-   P             [(Partial) Autocorrelation Function] [rev 81] [2009-11-27 21:07:22] [2e4ef2c1b76db9b31c0a03b96e94ad77] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





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=61278&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=61278&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61278&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 time2 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=61278&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=61278&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61278&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
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=61278&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=61278&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61278&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
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


Figures (Output of Computation)

Input Parameters & R Code

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')