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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 computationSun, 20 Dec 2009 09:09:30 -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/20/t1261325448grzzzg5imlu9t9l.htm/, Retrieved Sat, 04 May 2024 03:03:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69928, Retrieved Sat, 04 May 2024 03:03:51 +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 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]
-    D        [(Partial) Autocorrelation Function] [WS 8.1] [2009-11-27 19:35:53] [4a2be4899cba879e4eea9daa25281df8]
-    D          [(Partial) Autocorrelation Function] [PAPER 5] [2009-12-20 01:17:09] [4a2be4899cba879e4eea9daa25281df8]
-    D            [(Partial) Autocorrelation Function] [PAPER 12] [2009-12-20 01:36:32] [4a2be4899cba879e4eea9daa25281df8]
-    D              [(Partial) Autocorrelation Function] [PAPER 13] [2009-12-20 01:39:09] [4a2be4899cba879e4eea9daa25281df8]
-    D                  [(Partial) Autocorrelation Function] [paper 3] [2009-12-20 16:09:30] [71c065898bd1c08eef04509b4bcee039] [Current]
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Dataseries X:
31,48
29,90
33,84
39,12
33,70
25,09
51,44
45,59
52,52
48,56
41,75
49,59
32,75
33,38
35,65
37,03
35,68
20,97
58,55
54,96
65,54
51,57
51,15
46,64
35,70
33,25
35,19
41,67
34,87
21,21
56,13
49,23
59,72
48,10
47,47
50,50
40,06
34,15
36,86
46,36
36,58
23,87
57,28
56,39
57,66
62,30
48,93
51,17
39,64
33,21
38,13
43,29
30,60
21,96
48,03
46,15
50,74
48,11
38,39
44,11




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=69928&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=69928&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69928&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
10.5138933.56040.000424
20.5643433.90990.000145
30.306482.12340.019453
40.2143111.48480.072068
50.1206540.83590.203673
60.1249610.86580.195466
70.0325840.22570.411178
80.0186210.1290.448945
9-0.113165-0.7840.218438
10-0.170166-1.17890.122115
11-0.241681-1.67440.050276
12-0.373201-2.58560.006406
13-0.29095-2.01580.024721
14-0.229108-1.58730.059505
15-0.111511-0.77260.221781
16-0.062292-0.43160.333991
17-0.017102-0.11850.453089
18-0.024138-0.16720.433943
19-0.02342-0.16230.435893
20-0.001304-0.0090.496414
210.1209440.83790.203113
220.0271540.18810.425783
230.2536431.75730.042623
240.1707651.18310.121299
250.2680781.85730.034705
260.2001961.3870.085925
270.1521591.05420.148538
28-0.017335-0.12010.452453
290.0141350.09790.461198
30-0.091659-0.6350.264212
31-0.052134-0.36120.359769
32-0.099165-0.6870.247684
33-0.143847-0.99660.161977
34-0.155963-1.08050.14265
35-0.232137-1.60830.057165
36-0.237187-1.64330.05343

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.513893 & 3.5604 & 0.000424 \tabularnewline
2 & 0.564343 & 3.9099 & 0.000145 \tabularnewline
3 & 0.30648 & 2.1234 & 0.019453 \tabularnewline
4 & 0.214311 & 1.4848 & 0.072068 \tabularnewline
5 & 0.120654 & 0.8359 & 0.203673 \tabularnewline
6 & 0.124961 & 0.8658 & 0.195466 \tabularnewline
7 & 0.032584 & 0.2257 & 0.411178 \tabularnewline
8 & 0.018621 & 0.129 & 0.448945 \tabularnewline
9 & -0.113165 & -0.784 & 0.218438 \tabularnewline
10 & -0.170166 & -1.1789 & 0.122115 \tabularnewline
11 & -0.241681 & -1.6744 & 0.050276 \tabularnewline
12 & -0.373201 & -2.5856 & 0.006406 \tabularnewline
13 & -0.29095 & -2.0158 & 0.024721 \tabularnewline
14 & -0.229108 & -1.5873 & 0.059505 \tabularnewline
15 & -0.111511 & -0.7726 & 0.221781 \tabularnewline
16 & -0.062292 & -0.4316 & 0.333991 \tabularnewline
17 & -0.017102 & -0.1185 & 0.453089 \tabularnewline
18 & -0.024138 & -0.1672 & 0.433943 \tabularnewline
19 & -0.02342 & -0.1623 & 0.435893 \tabularnewline
20 & -0.001304 & -0.009 & 0.496414 \tabularnewline
21 & 0.120944 & 0.8379 & 0.203113 \tabularnewline
22 & 0.027154 & 0.1881 & 0.425783 \tabularnewline
23 & 0.253643 & 1.7573 & 0.042623 \tabularnewline
24 & 0.170765 & 1.1831 & 0.121299 \tabularnewline
25 & 0.268078 & 1.8573 & 0.034705 \tabularnewline
26 & 0.200196 & 1.387 & 0.085925 \tabularnewline
27 & 0.152159 & 1.0542 & 0.148538 \tabularnewline
28 & -0.017335 & -0.1201 & 0.452453 \tabularnewline
29 & 0.014135 & 0.0979 & 0.461198 \tabularnewline
30 & -0.091659 & -0.635 & 0.264212 \tabularnewline
31 & -0.052134 & -0.3612 & 0.359769 \tabularnewline
32 & -0.099165 & -0.687 & 0.247684 \tabularnewline
33 & -0.143847 & -0.9966 & 0.161977 \tabularnewline
34 & -0.155963 & -1.0805 & 0.14265 \tabularnewline
35 & -0.232137 & -1.6083 & 0.057165 \tabularnewline
36 & -0.237187 & -1.6433 & 0.05343 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69928&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]0.513893[/C][C]3.5604[/C][C]0.000424[/C][/ROW]
[ROW][C]2[/C][C]0.564343[/C][C]3.9099[/C][C]0.000145[/C][/ROW]
[ROW][C]3[/C][C]0.30648[/C][C]2.1234[/C][C]0.019453[/C][/ROW]
[ROW][C]4[/C][C]0.214311[/C][C]1.4848[/C][C]0.072068[/C][/ROW]
[ROW][C]5[/C][C]0.120654[/C][C]0.8359[/C][C]0.203673[/C][/ROW]
[ROW][C]6[/C][C]0.124961[/C][C]0.8658[/C][C]0.195466[/C][/ROW]
[ROW][C]7[/C][C]0.032584[/C][C]0.2257[/C][C]0.411178[/C][/ROW]
[ROW][C]8[/C][C]0.018621[/C][C]0.129[/C][C]0.448945[/C][/ROW]
[ROW][C]9[/C][C]-0.113165[/C][C]-0.784[/C][C]0.218438[/C][/ROW]
[ROW][C]10[/C][C]-0.170166[/C][C]-1.1789[/C][C]0.122115[/C][/ROW]
[ROW][C]11[/C][C]-0.241681[/C][C]-1.6744[/C][C]0.050276[/C][/ROW]
[ROW][C]12[/C][C]-0.373201[/C][C]-2.5856[/C][C]0.006406[/C][/ROW]
[ROW][C]13[/C][C]-0.29095[/C][C]-2.0158[/C][C]0.024721[/C][/ROW]
[ROW][C]14[/C][C]-0.229108[/C][C]-1.5873[/C][C]0.059505[/C][/ROW]
[ROW][C]15[/C][C]-0.111511[/C][C]-0.7726[/C][C]0.221781[/C][/ROW]
[ROW][C]16[/C][C]-0.062292[/C][C]-0.4316[/C][C]0.333991[/C][/ROW]
[ROW][C]17[/C][C]-0.017102[/C][C]-0.1185[/C][C]0.453089[/C][/ROW]
[ROW][C]18[/C][C]-0.024138[/C][C]-0.1672[/C][C]0.433943[/C][/ROW]
[ROW][C]19[/C][C]-0.02342[/C][C]-0.1623[/C][C]0.435893[/C][/ROW]
[ROW][C]20[/C][C]-0.001304[/C][C]-0.009[/C][C]0.496414[/C][/ROW]
[ROW][C]21[/C][C]0.120944[/C][C]0.8379[/C][C]0.203113[/C][/ROW]
[ROW][C]22[/C][C]0.027154[/C][C]0.1881[/C][C]0.425783[/C][/ROW]
[ROW][C]23[/C][C]0.253643[/C][C]1.7573[/C][C]0.042623[/C][/ROW]
[ROW][C]24[/C][C]0.170765[/C][C]1.1831[/C][C]0.121299[/C][/ROW]
[ROW][C]25[/C][C]0.268078[/C][C]1.8573[/C][C]0.034705[/C][/ROW]
[ROW][C]26[/C][C]0.200196[/C][C]1.387[/C][C]0.085925[/C][/ROW]
[ROW][C]27[/C][C]0.152159[/C][C]1.0542[/C][C]0.148538[/C][/ROW]
[ROW][C]28[/C][C]-0.017335[/C][C]-0.1201[/C][C]0.452453[/C][/ROW]
[ROW][C]29[/C][C]0.014135[/C][C]0.0979[/C][C]0.461198[/C][/ROW]
[ROW][C]30[/C][C]-0.091659[/C][C]-0.635[/C][C]0.264212[/C][/ROW]
[ROW][C]31[/C][C]-0.052134[/C][C]-0.3612[/C][C]0.359769[/C][/ROW]
[ROW][C]32[/C][C]-0.099165[/C][C]-0.687[/C][C]0.247684[/C][/ROW]
[ROW][C]33[/C][C]-0.143847[/C][C]-0.9966[/C][C]0.161977[/C][/ROW]
[ROW][C]34[/C][C]-0.155963[/C][C]-1.0805[/C][C]0.14265[/C][/ROW]
[ROW][C]35[/C][C]-0.232137[/C][C]-1.6083[/C][C]0.057165[/C][/ROW]
[ROW][C]36[/C][C]-0.237187[/C][C]-1.6433[/C][C]0.05343[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69928&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69928&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
10.5138933.56040.000424
20.5643433.90990.000145
30.306482.12340.019453
40.2143111.48480.072068
50.1206540.83590.203673
60.1249610.86580.195466
70.0325840.22570.411178
80.0186210.1290.448945
9-0.113165-0.7840.218438
10-0.170166-1.17890.122115
11-0.241681-1.67440.050276
12-0.373201-2.58560.006406
13-0.29095-2.01580.024721
14-0.229108-1.58730.059505
15-0.111511-0.77260.221781
16-0.062292-0.43160.333991
17-0.017102-0.11850.453089
18-0.024138-0.16720.433943
19-0.02342-0.16230.435893
20-0.001304-0.0090.496414
210.1209440.83790.203113
220.0271540.18810.425783
230.2536431.75730.042623
240.1707651.18310.121299
250.2680781.85730.034705
260.2001961.3870.085925
270.1521591.05420.148538
28-0.017335-0.12010.452453
290.0141350.09790.461198
30-0.091659-0.6350.264212
31-0.052134-0.36120.359769
32-0.099165-0.6870.247684
33-0.143847-0.99660.161977
34-0.155963-1.08050.14265
35-0.232137-1.60830.057165
36-0.237187-1.64330.05343







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5138933.56040.000424
20.4080052.82670.003418
3-0.122066-0.84570.200959
4-0.136816-0.94790.173967
50.0086510.05990.476227
60.1245560.8630.196228
7-0.070424-0.48790.313917
8-0.08943-0.61960.269228
9-0.156245-1.08250.142221
10-0.106941-0.74090.23118
11-0.047938-0.33210.37062
12-0.238549-1.65270.052458
130.040840.28290.389217
140.2179021.50970.068841
150.1481421.02640.154934
16-0.066658-0.46180.323149
17-0.06933-0.48030.316587
180.0384330.26630.395584
190.0035580.02460.490219
20-0.011187-0.07750.469271
210.1288740.89290.188192
22-0.193029-1.33730.093706
230.2071421.43510.078868
240.0329870.22850.410098
250.0060570.0420.483351
260.0315940.21890.413831
27-0.022169-0.15360.439289
28-0.232669-1.6120.056762
29-0.008095-0.05610.477755
300.0431950.29930.383015
31-0.098905-0.68520.248245
32-0.041554-0.28790.387334
330.018340.12710.44971
34-0.040338-0.27950.390542
35-0.009001-0.06240.475266
360.0096150.06660.473582

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.513893 & 3.5604 & 0.000424 \tabularnewline
2 & 0.408005 & 2.8267 & 0.003418 \tabularnewline
3 & -0.122066 & -0.8457 & 0.200959 \tabularnewline
4 & -0.136816 & -0.9479 & 0.173967 \tabularnewline
5 & 0.008651 & 0.0599 & 0.476227 \tabularnewline
6 & 0.124556 & 0.863 & 0.196228 \tabularnewline
7 & -0.070424 & -0.4879 & 0.313917 \tabularnewline
8 & -0.08943 & -0.6196 & 0.269228 \tabularnewline
9 & -0.156245 & -1.0825 & 0.142221 \tabularnewline
10 & -0.106941 & -0.7409 & 0.23118 \tabularnewline
11 & -0.047938 & -0.3321 & 0.37062 \tabularnewline
12 & -0.238549 & -1.6527 & 0.052458 \tabularnewline
13 & 0.04084 & 0.2829 & 0.389217 \tabularnewline
14 & 0.217902 & 1.5097 & 0.068841 \tabularnewline
15 & 0.148142 & 1.0264 & 0.154934 \tabularnewline
16 & -0.066658 & -0.4618 & 0.323149 \tabularnewline
17 & -0.06933 & -0.4803 & 0.316587 \tabularnewline
18 & 0.038433 & 0.2663 & 0.395584 \tabularnewline
19 & 0.003558 & 0.0246 & 0.490219 \tabularnewline
20 & -0.011187 & -0.0775 & 0.469271 \tabularnewline
21 & 0.128874 & 0.8929 & 0.188192 \tabularnewline
22 & -0.193029 & -1.3373 & 0.093706 \tabularnewline
23 & 0.207142 & 1.4351 & 0.078868 \tabularnewline
24 & 0.032987 & 0.2285 & 0.410098 \tabularnewline
25 & 0.006057 & 0.042 & 0.483351 \tabularnewline
26 & 0.031594 & 0.2189 & 0.413831 \tabularnewline
27 & -0.022169 & -0.1536 & 0.439289 \tabularnewline
28 & -0.232669 & -1.612 & 0.056762 \tabularnewline
29 & -0.008095 & -0.0561 & 0.477755 \tabularnewline
30 & 0.043195 & 0.2993 & 0.383015 \tabularnewline
31 & -0.098905 & -0.6852 & 0.248245 \tabularnewline
32 & -0.041554 & -0.2879 & 0.387334 \tabularnewline
33 & 0.01834 & 0.1271 & 0.44971 \tabularnewline
34 & -0.040338 & -0.2795 & 0.390542 \tabularnewline
35 & -0.009001 & -0.0624 & 0.475266 \tabularnewline
36 & 0.009615 & 0.0666 & 0.473582 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69928&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]0.513893[/C][C]3.5604[/C][C]0.000424[/C][/ROW]
[ROW][C]2[/C][C]0.408005[/C][C]2.8267[/C][C]0.003418[/C][/ROW]
[ROW][C]3[/C][C]-0.122066[/C][C]-0.8457[/C][C]0.200959[/C][/ROW]
[ROW][C]4[/C][C]-0.136816[/C][C]-0.9479[/C][C]0.173967[/C][/ROW]
[ROW][C]5[/C][C]0.008651[/C][C]0.0599[/C][C]0.476227[/C][/ROW]
[ROW][C]6[/C][C]0.124556[/C][C]0.863[/C][C]0.196228[/C][/ROW]
[ROW][C]7[/C][C]-0.070424[/C][C]-0.4879[/C][C]0.313917[/C][/ROW]
[ROW][C]8[/C][C]-0.08943[/C][C]-0.6196[/C][C]0.269228[/C][/ROW]
[ROW][C]9[/C][C]-0.156245[/C][C]-1.0825[/C][C]0.142221[/C][/ROW]
[ROW][C]10[/C][C]-0.106941[/C][C]-0.7409[/C][C]0.23118[/C][/ROW]
[ROW][C]11[/C][C]-0.047938[/C][C]-0.3321[/C][C]0.37062[/C][/ROW]
[ROW][C]12[/C][C]-0.238549[/C][C]-1.6527[/C][C]0.052458[/C][/ROW]
[ROW][C]13[/C][C]0.04084[/C][C]0.2829[/C][C]0.389217[/C][/ROW]
[ROW][C]14[/C][C]0.217902[/C][C]1.5097[/C][C]0.068841[/C][/ROW]
[ROW][C]15[/C][C]0.148142[/C][C]1.0264[/C][C]0.154934[/C][/ROW]
[ROW][C]16[/C][C]-0.066658[/C][C]-0.4618[/C][C]0.323149[/C][/ROW]
[ROW][C]17[/C][C]-0.06933[/C][C]-0.4803[/C][C]0.316587[/C][/ROW]
[ROW][C]18[/C][C]0.038433[/C][C]0.2663[/C][C]0.395584[/C][/ROW]
[ROW][C]19[/C][C]0.003558[/C][C]0.0246[/C][C]0.490219[/C][/ROW]
[ROW][C]20[/C][C]-0.011187[/C][C]-0.0775[/C][C]0.469271[/C][/ROW]
[ROW][C]21[/C][C]0.128874[/C][C]0.8929[/C][C]0.188192[/C][/ROW]
[ROW][C]22[/C][C]-0.193029[/C][C]-1.3373[/C][C]0.093706[/C][/ROW]
[ROW][C]23[/C][C]0.207142[/C][C]1.4351[/C][C]0.078868[/C][/ROW]
[ROW][C]24[/C][C]0.032987[/C][C]0.2285[/C][C]0.410098[/C][/ROW]
[ROW][C]25[/C][C]0.006057[/C][C]0.042[/C][C]0.483351[/C][/ROW]
[ROW][C]26[/C][C]0.031594[/C][C]0.2189[/C][C]0.413831[/C][/ROW]
[ROW][C]27[/C][C]-0.022169[/C][C]-0.1536[/C][C]0.439289[/C][/ROW]
[ROW][C]28[/C][C]-0.232669[/C][C]-1.612[/C][C]0.056762[/C][/ROW]
[ROW][C]29[/C][C]-0.008095[/C][C]-0.0561[/C][C]0.477755[/C][/ROW]
[ROW][C]30[/C][C]0.043195[/C][C]0.2993[/C][C]0.383015[/C][/ROW]
[ROW][C]31[/C][C]-0.098905[/C][C]-0.6852[/C][C]0.248245[/C][/ROW]
[ROW][C]32[/C][C]-0.041554[/C][C]-0.2879[/C][C]0.387334[/C][/ROW]
[ROW][C]33[/C][C]0.01834[/C][C]0.1271[/C][C]0.44971[/C][/ROW]
[ROW][C]34[/C][C]-0.040338[/C][C]-0.2795[/C][C]0.390542[/C][/ROW]
[ROW][C]35[/C][C]-0.009001[/C][C]-0.0624[/C][C]0.475266[/C][/ROW]
[ROW][C]36[/C][C]0.009615[/C][C]0.0666[/C][C]0.473582[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69928&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69928&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
10.5138933.56040.000424
20.4080052.82670.003418
3-0.122066-0.84570.200959
4-0.136816-0.94790.173967
50.0086510.05990.476227
60.1245560.8630.196228
7-0.070424-0.48790.313917
8-0.08943-0.61960.269228
9-0.156245-1.08250.142221
10-0.106941-0.74090.23118
11-0.047938-0.33210.37062
12-0.238549-1.65270.052458
130.040840.28290.389217
140.2179021.50970.068841
150.1481421.02640.154934
16-0.066658-0.46180.323149
17-0.06933-0.48030.316587
180.0384330.26630.395584
190.0035580.02460.490219
20-0.011187-0.07750.469271
210.1288740.89290.188192
22-0.193029-1.33730.093706
230.2071421.43510.078868
240.0329870.22850.410098
250.0060570.0420.483351
260.0315940.21890.413831
27-0.022169-0.15360.439289
28-0.232669-1.6120.056762
29-0.008095-0.05610.477755
300.0431950.29930.383015
31-0.098905-0.68520.248245
32-0.041554-0.28790.387334
330.018340.12710.44971
34-0.040338-0.27950.390542
35-0.009001-0.06240.475266
360.0096150.06660.473582



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')