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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 08:36:35 -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/t1259077068qp94l60l6s0wjwb.htm/, Retrieved Sat, 12 Oct 2024 12:54:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59123, Retrieved Sat, 12 Oct 2024 12:54:14 +0000
QR Codes:

Original text written by user:Uitleg in Word document
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact212
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 12:19:56] [b98453cac15ba1066b407e146608df68]
- R  D          [(Partial) Autocorrelation Function] [Bestedingen consu...] [2009-11-24 15:36:35] [8eb8270f5a1cfdf0409dcfcbf10be18b] [Current]
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Dataseries X:
96.96
93.11
95.62
98.30
96.38
100.82
99.06
94.03
102.07
99.31
98.64
101.82
99.14
97.63
100.06
101.32
101.49
105.43
105.09
99.48
108.53
104.34
106.10
107.35
103.00
104.50
105.17
104.84
106.18
108.86
107.77
102.74
112.63
106.26
108.86
111.38
106.85
107.86
107.94
111.38
111.29
113.72
111.88
109.87
113.72
111.71
114.81
112.05
111.54
110.87
110.87
115.48
111.63
116.24
113.56
106.01
110.45
107.77
108.61
108.19




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=59123&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=59123&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59123&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
10.6568474.55081.8e-05
20.5660593.92180.000139
30.5510593.81780.000193
40.2946662.04150.023359
50.1959421.35750.090482
60.1556681.07850.143101
70.0767420.53170.298699
80.043750.30310.381559
90.0026470.01830.492722
10-0.048731-0.33760.368561
11-0.007202-0.04990.480205
12-0.085983-0.59570.277084
13-0.14695-1.01810.156867
14-0.04437-0.30740.379933
15-0.097753-0.67730.250749
16-0.160682-1.11320.135575
17-0.052581-0.36430.35862
18-0.041522-0.28770.387419
19-0.050931-0.35290.362868
200.01950.13510.446548
210.0827920.57360.284459
220.035740.24760.402744
230.0868430.60170.275114
240.0376540.26090.397652
250.0670410.46450.322204
260.0471560.32670.372655
27-0.036169-0.25060.401601
28-0.020414-0.14140.444059
29-0.058067-0.40230.344625
30-0.144821-1.00340.160362
31-0.165813-1.14880.128169
32-0.162386-1.1250.133083
33-0.249909-1.73140.0449
34-0.244522-1.69410.048364
35-0.216172-1.49770.070381
36-0.272132-1.88540.032719

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.656847 & 4.5508 & 1.8e-05 \tabularnewline
2 & 0.566059 & 3.9218 & 0.000139 \tabularnewline
3 & 0.551059 & 3.8178 & 0.000193 \tabularnewline
4 & 0.294666 & 2.0415 & 0.023359 \tabularnewline
5 & 0.195942 & 1.3575 & 0.090482 \tabularnewline
6 & 0.155668 & 1.0785 & 0.143101 \tabularnewline
7 & 0.076742 & 0.5317 & 0.298699 \tabularnewline
8 & 0.04375 & 0.3031 & 0.381559 \tabularnewline
9 & 0.002647 & 0.0183 & 0.492722 \tabularnewline
10 & -0.048731 & -0.3376 & 0.368561 \tabularnewline
11 & -0.007202 & -0.0499 & 0.480205 \tabularnewline
12 & -0.085983 & -0.5957 & 0.277084 \tabularnewline
13 & -0.14695 & -1.0181 & 0.156867 \tabularnewline
14 & -0.04437 & -0.3074 & 0.379933 \tabularnewline
15 & -0.097753 & -0.6773 & 0.250749 \tabularnewline
16 & -0.160682 & -1.1132 & 0.135575 \tabularnewline
17 & -0.052581 & -0.3643 & 0.35862 \tabularnewline
18 & -0.041522 & -0.2877 & 0.387419 \tabularnewline
19 & -0.050931 & -0.3529 & 0.362868 \tabularnewline
20 & 0.0195 & 0.1351 & 0.446548 \tabularnewline
21 & 0.082792 & 0.5736 & 0.284459 \tabularnewline
22 & 0.03574 & 0.2476 & 0.402744 \tabularnewline
23 & 0.086843 & 0.6017 & 0.275114 \tabularnewline
24 & 0.037654 & 0.2609 & 0.397652 \tabularnewline
25 & 0.067041 & 0.4645 & 0.322204 \tabularnewline
26 & 0.047156 & 0.3267 & 0.372655 \tabularnewline
27 & -0.036169 & -0.2506 & 0.401601 \tabularnewline
28 & -0.020414 & -0.1414 & 0.444059 \tabularnewline
29 & -0.058067 & -0.4023 & 0.344625 \tabularnewline
30 & -0.144821 & -1.0034 & 0.160362 \tabularnewline
31 & -0.165813 & -1.1488 & 0.128169 \tabularnewline
32 & -0.162386 & -1.125 & 0.133083 \tabularnewline
33 & -0.249909 & -1.7314 & 0.0449 \tabularnewline
34 & -0.244522 & -1.6941 & 0.048364 \tabularnewline
35 & -0.216172 & -1.4977 & 0.070381 \tabularnewline
36 & -0.272132 & -1.8854 & 0.032719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59123&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]0.656847[/C][C]4.5508[/C][C]1.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.566059[/C][C]3.9218[/C][C]0.000139[/C][/ROW]
[ROW][C]3[/C][C]0.551059[/C][C]3.8178[/C][C]0.000193[/C][/ROW]
[ROW][C]4[/C][C]0.294666[/C][C]2.0415[/C][C]0.023359[/C][/ROW]
[ROW][C]5[/C][C]0.195942[/C][C]1.3575[/C][C]0.090482[/C][/ROW]
[ROW][C]6[/C][C]0.155668[/C][C]1.0785[/C][C]0.143101[/C][/ROW]
[ROW][C]7[/C][C]0.076742[/C][C]0.5317[/C][C]0.298699[/C][/ROW]
[ROW][C]8[/C][C]0.04375[/C][C]0.3031[/C][C]0.381559[/C][/ROW]
[ROW][C]9[/C][C]0.002647[/C][C]0.0183[/C][C]0.492722[/C][/ROW]
[ROW][C]10[/C][C]-0.048731[/C][C]-0.3376[/C][C]0.368561[/C][/ROW]
[ROW][C]11[/C][C]-0.007202[/C][C]-0.0499[/C][C]0.480205[/C][/ROW]
[ROW][C]12[/C][C]-0.085983[/C][C]-0.5957[/C][C]0.277084[/C][/ROW]
[ROW][C]13[/C][C]-0.14695[/C][C]-1.0181[/C][C]0.156867[/C][/ROW]
[ROW][C]14[/C][C]-0.04437[/C][C]-0.3074[/C][C]0.379933[/C][/ROW]
[ROW][C]15[/C][C]-0.097753[/C][C]-0.6773[/C][C]0.250749[/C][/ROW]
[ROW][C]16[/C][C]-0.160682[/C][C]-1.1132[/C][C]0.135575[/C][/ROW]
[ROW][C]17[/C][C]-0.052581[/C][C]-0.3643[/C][C]0.35862[/C][/ROW]
[ROW][C]18[/C][C]-0.041522[/C][C]-0.2877[/C][C]0.387419[/C][/ROW]
[ROW][C]19[/C][C]-0.050931[/C][C]-0.3529[/C][C]0.362868[/C][/ROW]
[ROW][C]20[/C][C]0.0195[/C][C]0.1351[/C][C]0.446548[/C][/ROW]
[ROW][C]21[/C][C]0.082792[/C][C]0.5736[/C][C]0.284459[/C][/ROW]
[ROW][C]22[/C][C]0.03574[/C][C]0.2476[/C][C]0.402744[/C][/ROW]
[ROW][C]23[/C][C]0.086843[/C][C]0.6017[/C][C]0.275114[/C][/ROW]
[ROW][C]24[/C][C]0.037654[/C][C]0.2609[/C][C]0.397652[/C][/ROW]
[ROW][C]25[/C][C]0.067041[/C][C]0.4645[/C][C]0.322204[/C][/ROW]
[ROW][C]26[/C][C]0.047156[/C][C]0.3267[/C][C]0.372655[/C][/ROW]
[ROW][C]27[/C][C]-0.036169[/C][C]-0.2506[/C][C]0.401601[/C][/ROW]
[ROW][C]28[/C][C]-0.020414[/C][C]-0.1414[/C][C]0.444059[/C][/ROW]
[ROW][C]29[/C][C]-0.058067[/C][C]-0.4023[/C][C]0.344625[/C][/ROW]
[ROW][C]30[/C][C]-0.144821[/C][C]-1.0034[/C][C]0.160362[/C][/ROW]
[ROW][C]31[/C][C]-0.165813[/C][C]-1.1488[/C][C]0.128169[/C][/ROW]
[ROW][C]32[/C][C]-0.162386[/C][C]-1.125[/C][C]0.133083[/C][/ROW]
[ROW][C]33[/C][C]-0.249909[/C][C]-1.7314[/C][C]0.0449[/C][/ROW]
[ROW][C]34[/C][C]-0.244522[/C][C]-1.6941[/C][C]0.048364[/C][/ROW]
[ROW][C]35[/C][C]-0.216172[/C][C]-1.4977[/C][C]0.070381[/C][/ROW]
[ROW][C]36[/C][C]-0.272132[/C][C]-1.8854[/C][C]0.032719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59123&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59123&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
10.6568474.55081.8e-05
20.5660593.92180.000139
30.5510593.81780.000193
40.2946662.04150.023359
50.1959421.35750.090482
60.1556681.07850.143101
70.0767420.53170.298699
80.043750.30310.381559
90.0026470.01830.492722
10-0.048731-0.33760.368561
11-0.007202-0.04990.480205
12-0.085983-0.59570.277084
13-0.14695-1.01810.156867
14-0.04437-0.30740.379933
15-0.097753-0.67730.250749
16-0.160682-1.11320.135575
17-0.052581-0.36430.35862
18-0.041522-0.28770.387419
19-0.050931-0.35290.362868
200.01950.13510.446548
210.0827920.57360.284459
220.035740.24760.402744
230.0868430.60170.275114
240.0376540.26090.397652
250.0670410.46450.322204
260.0471560.32670.372655
27-0.036169-0.25060.401601
28-0.020414-0.14140.444059
29-0.058067-0.40230.344625
30-0.144821-1.00340.160362
31-0.165813-1.14880.128169
32-0.162386-1.1250.133083
33-0.249909-1.73140.0449
34-0.244522-1.69410.048364
35-0.216172-1.49770.070381
36-0.272132-1.88540.032719







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6568474.55081.8e-05
20.2367611.64030.053737
30.2082431.44270.077793
4-0.323596-2.24190.014811
5-0.090894-0.62970.265929
60.0231560.16040.436609
70.1080480.74860.228881
80.0084030.05820.47691
9-0.09743-0.6750.251453
10-0.104413-0.72340.236474
110.130110.90140.185932
12-0.091308-0.63260.264998
13-0.120334-0.83370.20429
140.1259360.87250.193637
150.0152440.10560.458166
16-0.12205-0.84560.200989
170.0416960.28890.386959
180.0929480.6440.261332
190.0520420.36060.360006
20-0.016817-0.11650.453867
210.0844830.58530.280539
22-0.132952-0.92110.180798
230.0893540.61910.269402
24-0.127535-0.88360.190661
250.1287320.89190.188454
26-0.093853-0.65020.259321
27-0.01849-0.12810.449301
28-0.13358-0.92550.179677
29-0.004912-0.0340.486496
30-0.048199-0.33390.369943
31-0.044333-0.30710.380031
32-0.05558-0.38510.350944
33-0.062984-0.43640.332263
34-0.003594-0.02490.490119
350.0036770.02550.489892
36-0.10026-0.69460.24532

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.656847 & 4.5508 & 1.8e-05 \tabularnewline
2 & 0.236761 & 1.6403 & 0.053737 \tabularnewline
3 & 0.208243 & 1.4427 & 0.077793 \tabularnewline
4 & -0.323596 & -2.2419 & 0.014811 \tabularnewline
5 & -0.090894 & -0.6297 & 0.265929 \tabularnewline
6 & 0.023156 & 0.1604 & 0.436609 \tabularnewline
7 & 0.108048 & 0.7486 & 0.228881 \tabularnewline
8 & 0.008403 & 0.0582 & 0.47691 \tabularnewline
9 & -0.09743 & -0.675 & 0.251453 \tabularnewline
10 & -0.104413 & -0.7234 & 0.236474 \tabularnewline
11 & 0.13011 & 0.9014 & 0.185932 \tabularnewline
12 & -0.091308 & -0.6326 & 0.264998 \tabularnewline
13 & -0.120334 & -0.8337 & 0.20429 \tabularnewline
14 & 0.125936 & 0.8725 & 0.193637 \tabularnewline
15 & 0.015244 & 0.1056 & 0.458166 \tabularnewline
16 & -0.12205 & -0.8456 & 0.200989 \tabularnewline
17 & 0.041696 & 0.2889 & 0.386959 \tabularnewline
18 & 0.092948 & 0.644 & 0.261332 \tabularnewline
19 & 0.052042 & 0.3606 & 0.360006 \tabularnewline
20 & -0.016817 & -0.1165 & 0.453867 \tabularnewline
21 & 0.084483 & 0.5853 & 0.280539 \tabularnewline
22 & -0.132952 & -0.9211 & 0.180798 \tabularnewline
23 & 0.089354 & 0.6191 & 0.269402 \tabularnewline
24 & -0.127535 & -0.8836 & 0.190661 \tabularnewline
25 & 0.128732 & 0.8919 & 0.188454 \tabularnewline
26 & -0.093853 & -0.6502 & 0.259321 \tabularnewline
27 & -0.01849 & -0.1281 & 0.449301 \tabularnewline
28 & -0.13358 & -0.9255 & 0.179677 \tabularnewline
29 & -0.004912 & -0.034 & 0.486496 \tabularnewline
30 & -0.048199 & -0.3339 & 0.369943 \tabularnewline
31 & -0.044333 & -0.3071 & 0.380031 \tabularnewline
32 & -0.05558 & -0.3851 & 0.350944 \tabularnewline
33 & -0.062984 & -0.4364 & 0.332263 \tabularnewline
34 & -0.003594 & -0.0249 & 0.490119 \tabularnewline
35 & 0.003677 & 0.0255 & 0.489892 \tabularnewline
36 & -0.10026 & -0.6946 & 0.24532 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59123&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]0.656847[/C][C]4.5508[/C][C]1.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.236761[/C][C]1.6403[/C][C]0.053737[/C][/ROW]
[ROW][C]3[/C][C]0.208243[/C][C]1.4427[/C][C]0.077793[/C][/ROW]
[ROW][C]4[/C][C]-0.323596[/C][C]-2.2419[/C][C]0.014811[/C][/ROW]
[ROW][C]5[/C][C]-0.090894[/C][C]-0.6297[/C][C]0.265929[/C][/ROW]
[ROW][C]6[/C][C]0.023156[/C][C]0.1604[/C][C]0.436609[/C][/ROW]
[ROW][C]7[/C][C]0.108048[/C][C]0.7486[/C][C]0.228881[/C][/ROW]
[ROW][C]8[/C][C]0.008403[/C][C]0.0582[/C][C]0.47691[/C][/ROW]
[ROW][C]9[/C][C]-0.09743[/C][C]-0.675[/C][C]0.251453[/C][/ROW]
[ROW][C]10[/C][C]-0.104413[/C][C]-0.7234[/C][C]0.236474[/C][/ROW]
[ROW][C]11[/C][C]0.13011[/C][C]0.9014[/C][C]0.185932[/C][/ROW]
[ROW][C]12[/C][C]-0.091308[/C][C]-0.6326[/C][C]0.264998[/C][/ROW]
[ROW][C]13[/C][C]-0.120334[/C][C]-0.8337[/C][C]0.20429[/C][/ROW]
[ROW][C]14[/C][C]0.125936[/C][C]0.8725[/C][C]0.193637[/C][/ROW]
[ROW][C]15[/C][C]0.015244[/C][C]0.1056[/C][C]0.458166[/C][/ROW]
[ROW][C]16[/C][C]-0.12205[/C][C]-0.8456[/C][C]0.200989[/C][/ROW]
[ROW][C]17[/C][C]0.041696[/C][C]0.2889[/C][C]0.386959[/C][/ROW]
[ROW][C]18[/C][C]0.092948[/C][C]0.644[/C][C]0.261332[/C][/ROW]
[ROW][C]19[/C][C]0.052042[/C][C]0.3606[/C][C]0.360006[/C][/ROW]
[ROW][C]20[/C][C]-0.016817[/C][C]-0.1165[/C][C]0.453867[/C][/ROW]
[ROW][C]21[/C][C]0.084483[/C][C]0.5853[/C][C]0.280539[/C][/ROW]
[ROW][C]22[/C][C]-0.132952[/C][C]-0.9211[/C][C]0.180798[/C][/ROW]
[ROW][C]23[/C][C]0.089354[/C][C]0.6191[/C][C]0.269402[/C][/ROW]
[ROW][C]24[/C][C]-0.127535[/C][C]-0.8836[/C][C]0.190661[/C][/ROW]
[ROW][C]25[/C][C]0.128732[/C][C]0.8919[/C][C]0.188454[/C][/ROW]
[ROW][C]26[/C][C]-0.093853[/C][C]-0.6502[/C][C]0.259321[/C][/ROW]
[ROW][C]27[/C][C]-0.01849[/C][C]-0.1281[/C][C]0.449301[/C][/ROW]
[ROW][C]28[/C][C]-0.13358[/C][C]-0.9255[/C][C]0.179677[/C][/ROW]
[ROW][C]29[/C][C]-0.004912[/C][C]-0.034[/C][C]0.486496[/C][/ROW]
[ROW][C]30[/C][C]-0.048199[/C][C]-0.3339[/C][C]0.369943[/C][/ROW]
[ROW][C]31[/C][C]-0.044333[/C][C]-0.3071[/C][C]0.380031[/C][/ROW]
[ROW][C]32[/C][C]-0.05558[/C][C]-0.3851[/C][C]0.350944[/C][/ROW]
[ROW][C]33[/C][C]-0.062984[/C][C]-0.4364[/C][C]0.332263[/C][/ROW]
[ROW][C]34[/C][C]-0.003594[/C][C]-0.0249[/C][C]0.490119[/C][/ROW]
[ROW][C]35[/C][C]0.003677[/C][C]0.0255[/C][C]0.489892[/C][/ROW]
[ROW][C]36[/C][C]-0.10026[/C][C]-0.6946[/C][C]0.24532[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59123&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59123&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
10.6568474.55081.8e-05
20.2367611.64030.053737
30.2082431.44270.077793
4-0.323596-2.24190.014811
5-0.090894-0.62970.265929
60.0231560.16040.436609
70.1080480.74860.228881
80.0084030.05820.47691
9-0.09743-0.6750.251453
10-0.104413-0.72340.236474
110.130110.90140.185932
12-0.091308-0.63260.264998
13-0.120334-0.83370.20429
140.1259360.87250.193637
150.0152440.10560.458166
16-0.12205-0.84560.200989
170.0416960.28890.386959
180.0929480.6440.261332
190.0520420.36060.360006
20-0.016817-0.11650.453867
210.0844830.58530.280539
22-0.132952-0.92110.180798
230.0893540.61910.269402
24-0.127535-0.88360.190661
250.1287320.89190.188454
26-0.093853-0.65020.259321
27-0.01849-0.12810.449301
28-0.13358-0.92550.179677
29-0.004912-0.0340.486496
30-0.048199-0.33390.369943
31-0.044333-0.30710.380031
32-0.05558-0.38510.350944
33-0.062984-0.43640.332263
34-0.003594-0.02490.490119
350.0036770.02550.489892
36-0.10026-0.69460.24532



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')