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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 computationThu, 10 Dec 2009 10:17:33 -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/t1260465487i25i5s7x16il97u.htm/, Retrieved Thu, 25 Apr 2024 15:57:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65619, Retrieved Thu, 25 Apr 2024 15:57:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

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]
- R  D        [(Partial) Autocorrelation Function] [workshop 8] [2009-11-26 18:42:50] [3d8acb8ffdb376c5fec19e610f8198c2]
-   PD            [(Partial) Autocorrelation Function] [verbetering] [2009-12-10 17:17:33] [5edea6bc5a9a9483633d9320282a2734] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102.86
102.55
102.28
102.26
102.57
103.08
102.76
102.51
102.87
103.14
103.12
103.16
102.48
102.57
102.88
102.63
102.38
101.69
101.96
102.19
101.87
101.6
101.63
101.22
101.21
101.49
101.64
101.66
101.77
101.82
101.78
101.28
101.29
101.37
101.12
101.51
102.24
102.94
103.09
103.46
103.64
104.39
104.15
105.21
105.8
105.91
105.39
105.46
104.72
103.14
102.63
102.32
101.93
100.62
100.6
99.63
98.9
98.32
99.22
98.81

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65619&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]0 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=65619&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65619&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2870272.20470.015694
20.2118081.62690.054541
30.2071281.5910.058479
40.3500462.68880.004654
5-0.017538-0.13470.446651
60.0742850.57060.28522
70.1125670.86460.195368
8-0.016403-0.1260.450083
9-0.190501-1.46330.074351
10-0.145086-1.11440.134808
110.002970.02280.490937
12-0.415377-3.19060.001138
13-0.251563-1.93230.029064
14-0.108019-0.82970.205024
150.0071560.0550.478176
16-0.209744-1.61110.056251
17-0.023136-0.17770.42978
18-0.061321-0.4710.319684
19-0.024216-0.1860.42654
20-0.184304-1.41570.081065
21-0.031996-0.24580.403357
220.044890.34480.365733
23-0.064546-0.49580.310944
24-0.116016-0.89110.188238
250.0415330.3190.375418
26-0.019017-0.14610.44218
27-0.084572-0.64960.259234
280.0025750.01980.492142
290.0247340.190.424986
300.0204210.15690.437948
31-0.029876-0.22950.409644
320.1386951.06530.145532
330.117840.90510.184534
340.0370060.28430.388606
35-0.029143-0.22390.411823
360.1131090.86880.194238

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.287027 & 2.2047 & 0.015694 \tabularnewline
2 & 0.211808 & 1.6269 & 0.054541 \tabularnewline
3 & 0.207128 & 1.591 & 0.058479 \tabularnewline
4 & 0.350046 & 2.6888 & 0.004654 \tabularnewline
5 & -0.017538 & -0.1347 & 0.446651 \tabularnewline
6 & 0.074285 & 0.5706 & 0.28522 \tabularnewline
7 & 0.112567 & 0.8646 & 0.195368 \tabularnewline
8 & -0.016403 & -0.126 & 0.450083 \tabularnewline
9 & -0.190501 & -1.4633 & 0.074351 \tabularnewline
10 & -0.145086 & -1.1144 & 0.134808 \tabularnewline
11 & 0.00297 & 0.0228 & 0.490937 \tabularnewline
12 & -0.415377 & -3.1906 & 0.001138 \tabularnewline
13 & -0.251563 & -1.9323 & 0.029064 \tabularnewline
14 & -0.108019 & -0.8297 & 0.205024 \tabularnewline
15 & 0.007156 & 0.055 & 0.478176 \tabularnewline
16 & -0.209744 & -1.6111 & 0.056251 \tabularnewline
17 & -0.023136 & -0.1777 & 0.42978 \tabularnewline
18 & -0.061321 & -0.471 & 0.319684 \tabularnewline
19 & -0.024216 & -0.186 & 0.42654 \tabularnewline
20 & -0.184304 & -1.4157 & 0.081065 \tabularnewline
21 & -0.031996 & -0.2458 & 0.403357 \tabularnewline
22 & 0.04489 & 0.3448 & 0.365733 \tabularnewline
23 & -0.064546 & -0.4958 & 0.310944 \tabularnewline
24 & -0.116016 & -0.8911 & 0.188238 \tabularnewline
25 & 0.041533 & 0.319 & 0.375418 \tabularnewline
26 & -0.019017 & -0.1461 & 0.44218 \tabularnewline
27 & -0.084572 & -0.6496 & 0.259234 \tabularnewline
28 & 0.002575 & 0.0198 & 0.492142 \tabularnewline
29 & 0.024734 & 0.19 & 0.424986 \tabularnewline
30 & 0.020421 & 0.1569 & 0.437948 \tabularnewline
31 & -0.029876 & -0.2295 & 0.409644 \tabularnewline
32 & 0.138695 & 1.0653 & 0.145532 \tabularnewline
33 & 0.11784 & 0.9051 & 0.184534 \tabularnewline
34 & 0.037006 & 0.2843 & 0.388606 \tabularnewline
35 & -0.029143 & -0.2239 & 0.411823 \tabularnewline
36 & 0.113109 & 0.8688 & 0.194238 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65619&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]0.287027[/C][C]2.2047[/C][C]0.015694[/C][/ROW]
[ROW][C]2[/C][C]0.211808[/C][C]1.6269[/C][C]0.054541[/C][/ROW]
[ROW][C]3[/C][C]0.207128[/C][C]1.591[/C][C]0.058479[/C][/ROW]
[ROW][C]4[/C][C]0.350046[/C][C]2.6888[/C][C]0.004654[/C][/ROW]
[ROW][C]5[/C][C]-0.017538[/C][C]-0.1347[/C][C]0.446651[/C][/ROW]
[ROW][C]6[/C][C]0.074285[/C][C]0.5706[/C][C]0.28522[/C][/ROW]
[ROW][C]7[/C][C]0.112567[/C][C]0.8646[/C][C]0.195368[/C][/ROW]
[ROW][C]8[/C][C]-0.016403[/C][C]-0.126[/C][C]0.450083[/C][/ROW]
[ROW][C]9[/C][C]-0.190501[/C][C]-1.4633[/C][C]0.074351[/C][/ROW]
[ROW][C]10[/C][C]-0.145086[/C][C]-1.1144[/C][C]0.134808[/C][/ROW]
[ROW][C]11[/C][C]0.00297[/C][C]0.0228[/C][C]0.490937[/C][/ROW]
[ROW][C]12[/C][C]-0.415377[/C][C]-3.1906[/C][C]0.001138[/C][/ROW]
[ROW][C]13[/C][C]-0.251563[/C][C]-1.9323[/C][C]0.029064[/C][/ROW]
[ROW][C]14[/C][C]-0.108019[/C][C]-0.8297[/C][C]0.205024[/C][/ROW]
[ROW][C]15[/C][C]0.007156[/C][C]0.055[/C][C]0.478176[/C][/ROW]
[ROW][C]16[/C][C]-0.209744[/C][C]-1.6111[/C][C]0.056251[/C][/ROW]
[ROW][C]17[/C][C]-0.023136[/C][C]-0.1777[/C][C]0.42978[/C][/ROW]
[ROW][C]18[/C][C]-0.061321[/C][C]-0.471[/C][C]0.319684[/C][/ROW]
[ROW][C]19[/C][C]-0.024216[/C][C]-0.186[/C][C]0.42654[/C][/ROW]
[ROW][C]20[/C][C]-0.184304[/C][C]-1.4157[/C][C]0.081065[/C][/ROW]
[ROW][C]21[/C][C]-0.031996[/C][C]-0.2458[/C][C]0.403357[/C][/ROW]
[ROW][C]22[/C][C]0.04489[/C][C]0.3448[/C][C]0.365733[/C][/ROW]
[ROW][C]23[/C][C]-0.064546[/C][C]-0.4958[/C][C]0.310944[/C][/ROW]
[ROW][C]24[/C][C]-0.116016[/C][C]-0.8911[/C][C]0.188238[/C][/ROW]
[ROW][C]25[/C][C]0.041533[/C][C]0.319[/C][C]0.375418[/C][/ROW]
[ROW][C]26[/C][C]-0.019017[/C][C]-0.1461[/C][C]0.44218[/C][/ROW]
[ROW][C]27[/C][C]-0.084572[/C][C]-0.6496[/C][C]0.259234[/C][/ROW]
[ROW][C]28[/C][C]0.002575[/C][C]0.0198[/C][C]0.492142[/C][/ROW]
[ROW][C]29[/C][C]0.024734[/C][C]0.19[/C][C]0.424986[/C][/ROW]
[ROW][C]30[/C][C]0.020421[/C][C]0.1569[/C][C]0.437948[/C][/ROW]
[ROW][C]31[/C][C]-0.029876[/C][C]-0.2295[/C][C]0.409644[/C][/ROW]
[ROW][C]32[/C][C]0.138695[/C][C]1.0653[/C][C]0.145532[/C][/ROW]
[ROW][C]33[/C][C]0.11784[/C][C]0.9051[/C][C]0.184534[/C][/ROW]
[ROW][C]34[/C][C]0.037006[/C][C]0.2843[/C][C]0.388606[/C][/ROW]
[ROW][C]35[/C][C]-0.029143[/C][C]-0.2239[/C][C]0.411823[/C][/ROW]
[ROW][C]36[/C][C]0.113109[/C][C]0.8688[/C][C]0.194238[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65619&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65619&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
10.2870272.20470.015694
20.2118081.62690.054541
30.2071281.5910.058479
40.3500462.68880.004654
5-0.017538-0.13470.446651
60.0742850.57060.28522
70.1125670.86460.195368
8-0.016403-0.1260.450083
9-0.190501-1.46330.074351
10-0.145086-1.11440.134808
110.002970.02280.490937
12-0.415377-3.19060.001138
13-0.251563-1.93230.029064
14-0.108019-0.82970.205024
150.0071560.0550.478176
16-0.209744-1.61110.056251
17-0.023136-0.17770.42978
18-0.061321-0.4710.319684
19-0.024216-0.1860.42654
20-0.184304-1.41570.081065
21-0.031996-0.24580.403357
220.044890.34480.365733
23-0.064546-0.49580.310944
24-0.116016-0.89110.188238
250.0415330.3190.375418
26-0.019017-0.14610.44218
27-0.084572-0.64960.259234
280.0025750.01980.492142
290.0247340.190.424986
300.0204210.15690.437948
31-0.029876-0.22950.409644
320.1386951.06530.145532
330.117840.90510.184534
340.0370060.28430.388606
35-0.029143-0.22390.411823
360.1131090.86880.194238






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2870272.20470.015694
20.1410431.08340.141525
30.127230.97730.166213
40.2745792.10910.019596
5-0.23747-1.8240.036606
60.0370660.28470.388433
70.0545640.41910.338329
8-0.169299-1.30040.099259
9-0.118632-0.91120.182942
10-0.136568-1.0490.149229
110.1073970.82490.206366
12-0.419203-3.220.001043
130.0553850.42540.336038
140.1051440.80760.211274
150.0730830.56140.288338
160.1237110.95020.172933
17-0.054474-0.41840.338579
18-0.066943-0.51420.304516
190.0174510.1340.446913
20-0.206838-1.58880.058731
21-0.107061-0.82240.207094
220.0140360.10780.457255
23-0.020765-0.15950.436911
24-0.195774-1.50380.068988
250.0805840.6190.269157
26-0.041603-0.31960.375217
270.1120120.86040.196532
280.1060170.81430.209365
29-0.050891-0.39090.348638
300.0095560.07340.470869
31-0.007907-0.06070.475887
320.0407530.3130.377682
33-0.091275-0.70110.243
34-0.028292-0.21730.414355
35-0.058403-0.44860.327681
36-0.158515-1.21760.114116

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.287027 & 2.2047 & 0.015694 \tabularnewline
2 & 0.141043 & 1.0834 & 0.141525 \tabularnewline
3 & 0.12723 & 0.9773 & 0.166213 \tabularnewline
4 & 0.274579 & 2.1091 & 0.019596 \tabularnewline
5 & -0.23747 & -1.824 & 0.036606 \tabularnewline
6 & 0.037066 & 0.2847 & 0.388433 \tabularnewline
7 & 0.054564 & 0.4191 & 0.338329 \tabularnewline
8 & -0.169299 & -1.3004 & 0.099259 \tabularnewline
9 & -0.118632 & -0.9112 & 0.182942 \tabularnewline
10 & -0.136568 & -1.049 & 0.149229 \tabularnewline
11 & 0.107397 & 0.8249 & 0.206366 \tabularnewline
12 & -0.419203 & -3.22 & 0.001043 \tabularnewline
13 & 0.055385 & 0.4254 & 0.336038 \tabularnewline
14 & 0.105144 & 0.8076 & 0.211274 \tabularnewline
15 & 0.073083 & 0.5614 & 0.288338 \tabularnewline
16 & 0.123711 & 0.9502 & 0.172933 \tabularnewline
17 & -0.054474 & -0.4184 & 0.338579 \tabularnewline
18 & -0.066943 & -0.5142 & 0.304516 \tabularnewline
19 & 0.017451 & 0.134 & 0.446913 \tabularnewline
20 & -0.206838 & -1.5888 & 0.058731 \tabularnewline
21 & -0.107061 & -0.8224 & 0.207094 \tabularnewline
22 & 0.014036 & 0.1078 & 0.457255 \tabularnewline
23 & -0.020765 & -0.1595 & 0.436911 \tabularnewline
24 & -0.195774 & -1.5038 & 0.068988 \tabularnewline
25 & 0.080584 & 0.619 & 0.269157 \tabularnewline
26 & -0.041603 & -0.3196 & 0.375217 \tabularnewline
27 & 0.112012 & 0.8604 & 0.196532 \tabularnewline
28 & 0.106017 & 0.8143 & 0.209365 \tabularnewline
29 & -0.050891 & -0.3909 & 0.348638 \tabularnewline
30 & 0.009556 & 0.0734 & 0.470869 \tabularnewline
31 & -0.007907 & -0.0607 & 0.475887 \tabularnewline
32 & 0.040753 & 0.313 & 0.377682 \tabularnewline
33 & -0.091275 & -0.7011 & 0.243 \tabularnewline
34 & -0.028292 & -0.2173 & 0.414355 \tabularnewline
35 & -0.058403 & -0.4486 & 0.327681 \tabularnewline
36 & -0.158515 & -1.2176 & 0.114116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65619&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]0.287027[/C][C]2.2047[/C][C]0.015694[/C][/ROW]
[ROW][C]2[/C][C]0.141043[/C][C]1.0834[/C][C]0.141525[/C][/ROW]
[ROW][C]3[/C][C]0.12723[/C][C]0.9773[/C][C]0.166213[/C][/ROW]
[ROW][C]4[/C][C]0.274579[/C][C]2.1091[/C][C]0.019596[/C][/ROW]
[ROW][C]5[/C][C]-0.23747[/C][C]-1.824[/C][C]0.036606[/C][/ROW]
[ROW][C]6[/C][C]0.037066[/C][C]0.2847[/C][C]0.388433[/C][/ROW]
[ROW][C]7[/C][C]0.054564[/C][C]0.4191[/C][C]0.338329[/C][/ROW]
[ROW][C]8[/C][C]-0.169299[/C][C]-1.3004[/C][C]0.099259[/C][/ROW]
[ROW][C]9[/C][C]-0.118632[/C][C]-0.9112[/C][C]0.182942[/C][/ROW]
[ROW][C]10[/C][C]-0.136568[/C][C]-1.049[/C][C]0.149229[/C][/ROW]
[ROW][C]11[/C][C]0.107397[/C][C]0.8249[/C][C]0.206366[/C][/ROW]
[ROW][C]12[/C][C]-0.419203[/C][C]-3.22[/C][C]0.001043[/C][/ROW]
[ROW][C]13[/C][C]0.055385[/C][C]0.4254[/C][C]0.336038[/C][/ROW]
[ROW][C]14[/C][C]0.105144[/C][C]0.8076[/C][C]0.211274[/C][/ROW]
[ROW][C]15[/C][C]0.073083[/C][C]0.5614[/C][C]0.288338[/C][/ROW]
[ROW][C]16[/C][C]0.123711[/C][C]0.9502[/C][C]0.172933[/C][/ROW]
[ROW][C]17[/C][C]-0.054474[/C][C]-0.4184[/C][C]0.338579[/C][/ROW]
[ROW][C]18[/C][C]-0.066943[/C][C]-0.5142[/C][C]0.304516[/C][/ROW]
[ROW][C]19[/C][C]0.017451[/C][C]0.134[/C][C]0.446913[/C][/ROW]
[ROW][C]20[/C][C]-0.206838[/C][C]-1.5888[/C][C]0.058731[/C][/ROW]
[ROW][C]21[/C][C]-0.107061[/C][C]-0.8224[/C][C]0.207094[/C][/ROW]
[ROW][C]22[/C][C]0.014036[/C][C]0.1078[/C][C]0.457255[/C][/ROW]
[ROW][C]23[/C][C]-0.020765[/C][C]-0.1595[/C][C]0.436911[/C][/ROW]
[ROW][C]24[/C][C]-0.195774[/C][C]-1.5038[/C][C]0.068988[/C][/ROW]
[ROW][C]25[/C][C]0.080584[/C][C]0.619[/C][C]0.269157[/C][/ROW]
[ROW][C]26[/C][C]-0.041603[/C][C]-0.3196[/C][C]0.375217[/C][/ROW]
[ROW][C]27[/C][C]0.112012[/C][C]0.8604[/C][C]0.196532[/C][/ROW]
[ROW][C]28[/C][C]0.106017[/C][C]0.8143[/C][C]0.209365[/C][/ROW]
[ROW][C]29[/C][C]-0.050891[/C][C]-0.3909[/C][C]0.348638[/C][/ROW]
[ROW][C]30[/C][C]0.009556[/C][C]0.0734[/C][C]0.470869[/C][/ROW]
[ROW][C]31[/C][C]-0.007907[/C][C]-0.0607[/C][C]0.475887[/C][/ROW]
[ROW][C]32[/C][C]0.040753[/C][C]0.313[/C][C]0.377682[/C][/ROW]
[ROW][C]33[/C][C]-0.091275[/C][C]-0.7011[/C][C]0.243[/C][/ROW]
[ROW][C]34[/C][C]-0.028292[/C][C]-0.2173[/C][C]0.414355[/C][/ROW]
[ROW][C]35[/C][C]-0.058403[/C][C]-0.4486[/C][C]0.327681[/C][/ROW]
[ROW][C]36[/C][C]-0.158515[/C][C]-1.2176[/C][C]0.114116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65619&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65619&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
10.2870272.20470.015694
20.1410431.08340.141525
30.127230.97730.166213
40.2745792.10910.019596
5-0.23747-1.8240.036606
60.0370660.28470.388433
70.0545640.41910.338329
8-0.169299-1.30040.099259
9-0.118632-0.91120.182942
10-0.136568-1.0490.149229
110.1073970.82490.206366
12-0.419203-3.220.001043
130.0553850.42540.336038
140.1051440.80760.211274
150.0730830.56140.288338
160.1237110.95020.172933
17-0.054474-0.41840.338579
18-0.066943-0.51420.304516
190.0174510.1340.446913
20-0.206838-1.58880.058731
21-0.107061-0.82240.207094
220.0140360.10780.457255
23-0.020765-0.15950.436911
24-0.195774-1.50380.068988
250.0805840.6190.269157
26-0.041603-0.31960.375217
270.1120120.86040.196532
280.1060170.81430.209365
29-0.050891-0.39090.348638
300.0095560.07340.470869
31-0.007907-0.06070.475887
320.0407530.3130.377682
33-0.091275-0.70110.243
34-0.028292-0.21730.414355
35-0.058403-0.44860.327681
36-0.158515-1.21760.114116


Figures (Output of Computation)

Input Parameters & R Code

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