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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, 18 Dec 2009 04:51:01 -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/18/t1261137158e15gmm99r17abn3.htm/, Retrieved Sat, 27 Apr 2024 05:24:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69259, Retrieved Sat, 27 Apr 2024 05:24:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-24 09:58:46] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:49:26] [fef2f8976fa1eef1b54e2cee317fe737]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-18 11:51:01] [2ffc7e281e02b99889abd2ccc65ed6c3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
120.9
119.6
125.9
116.1
107.5
116.7
112.5
113
126.4
114.1
112.5
112.4
113.1
116.3
111.7
118.8
116.5
125.1
113.1
119.6
114.4
114
117.8
117
120.9
115
117.3
119.4
114.9
125.8
117.6
117.6
114.9
121.9
117
106.4
110.5
113.6
114.2
125.4
124.6
120.2
120.8
111.4
124.1
120.2
125.5
116
117
105.7
102
106.4
96.9
107.6
98.8
101.1
105.7
104.6
103.2
101.6

Tables (Output of Computation)





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=69259&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=69259&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69259&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.455275-3.12120.001539
20.2259931.54930.064005
3-0.213269-1.46210.075185
40.031040.21280.416201
5-0.181045-1.24120.11035
60.07390.50660.30739
70.1854091.27110.104974
8-0.133213-0.91330.182883
90.1638931.12360.133446
10-0.241607-1.65640.052154
110.2655361.82040.037533
12-0.382455-2.6220.005872
130.1049160.71930.237769
140.0070270.04820.48089
150.0669350.45890.324216
160.0665790.45640.325086
170.0009220.00630.497493
180.1232980.84530.201115
19-0.316521-2.170.017549
200.0583610.40010.345448
210.063280.43380.333199
22-0.029239-0.20050.420997
230.1321260.90580.184828
24-0.054021-0.37040.356392
250.0761050.52170.302148
26-0.171067-1.17280.123398
270.1439220.98670.164427
28-0.214917-1.47340.073655
290.2099481.43930.078342
30-0.175042-1.20.118071
310.1995221.36790.088931
32-0.00453-0.03110.487679
33-0.085245-0.58440.280871
340.0290330.1990.421544
35-0.115023-0.78860.217165
360.0246340.16890.433306

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.455275 & -3.1212 & 0.001539 \tabularnewline
2 & 0.225993 & 1.5493 & 0.064005 \tabularnewline
3 & -0.213269 & -1.4621 & 0.075185 \tabularnewline
4 & 0.03104 & 0.2128 & 0.416201 \tabularnewline
5 & -0.181045 & -1.2412 & 0.11035 \tabularnewline
6 & 0.0739 & 0.5066 & 0.30739 \tabularnewline
7 & 0.185409 & 1.2711 & 0.104974 \tabularnewline
8 & -0.133213 & -0.9133 & 0.182883 \tabularnewline
9 & 0.163893 & 1.1236 & 0.133446 \tabularnewline
10 & -0.241607 & -1.6564 & 0.052154 \tabularnewline
11 & 0.265536 & 1.8204 & 0.037533 \tabularnewline
12 & -0.382455 & -2.622 & 0.005872 \tabularnewline
13 & 0.104916 & 0.7193 & 0.237769 \tabularnewline
14 & 0.007027 & 0.0482 & 0.48089 \tabularnewline
15 & 0.066935 & 0.4589 & 0.324216 \tabularnewline
16 & 0.066579 & 0.4564 & 0.325086 \tabularnewline
17 & 0.000922 & 0.0063 & 0.497493 \tabularnewline
18 & 0.123298 & 0.8453 & 0.201115 \tabularnewline
19 & -0.316521 & -2.17 & 0.017549 \tabularnewline
20 & 0.058361 & 0.4001 & 0.345448 \tabularnewline
21 & 0.06328 & 0.4338 & 0.333199 \tabularnewline
22 & -0.029239 & -0.2005 & 0.420997 \tabularnewline
23 & 0.132126 & 0.9058 & 0.184828 \tabularnewline
24 & -0.054021 & -0.3704 & 0.356392 \tabularnewline
25 & 0.076105 & 0.5217 & 0.302148 \tabularnewline
26 & -0.171067 & -1.1728 & 0.123398 \tabularnewline
27 & 0.143922 & 0.9867 & 0.164427 \tabularnewline
28 & -0.214917 & -1.4734 & 0.073655 \tabularnewline
29 & 0.209948 & 1.4393 & 0.078342 \tabularnewline
30 & -0.175042 & -1.2 & 0.118071 \tabularnewline
31 & 0.199522 & 1.3679 & 0.088931 \tabularnewline
32 & -0.00453 & -0.0311 & 0.487679 \tabularnewline
33 & -0.085245 & -0.5844 & 0.280871 \tabularnewline
34 & 0.029033 & 0.199 & 0.421544 \tabularnewline
35 & -0.115023 & -0.7886 & 0.217165 \tabularnewline
36 & 0.024634 & 0.1689 & 0.433306 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69259&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]-0.455275[/C][C]-3.1212[/C][C]0.001539[/C][/ROW]
[ROW][C]2[/C][C]0.225993[/C][C]1.5493[/C][C]0.064005[/C][/ROW]
[ROW][C]3[/C][C]-0.213269[/C][C]-1.4621[/C][C]0.075185[/C][/ROW]
[ROW][C]4[/C][C]0.03104[/C][C]0.2128[/C][C]0.416201[/C][/ROW]
[ROW][C]5[/C][C]-0.181045[/C][C]-1.2412[/C][C]0.11035[/C][/ROW]
[ROW][C]6[/C][C]0.0739[/C][C]0.5066[/C][C]0.30739[/C][/ROW]
[ROW][C]7[/C][C]0.185409[/C][C]1.2711[/C][C]0.104974[/C][/ROW]
[ROW][C]8[/C][C]-0.133213[/C][C]-0.9133[/C][C]0.182883[/C][/ROW]
[ROW][C]9[/C][C]0.163893[/C][C]1.1236[/C][C]0.133446[/C][/ROW]
[ROW][C]10[/C][C]-0.241607[/C][C]-1.6564[/C][C]0.052154[/C][/ROW]
[ROW][C]11[/C][C]0.265536[/C][C]1.8204[/C][C]0.037533[/C][/ROW]
[ROW][C]12[/C][C]-0.382455[/C][C]-2.622[/C][C]0.005872[/C][/ROW]
[ROW][C]13[/C][C]0.104916[/C][C]0.7193[/C][C]0.237769[/C][/ROW]
[ROW][C]14[/C][C]0.007027[/C][C]0.0482[/C][C]0.48089[/C][/ROW]
[ROW][C]15[/C][C]0.066935[/C][C]0.4589[/C][C]0.324216[/C][/ROW]
[ROW][C]16[/C][C]0.066579[/C][C]0.4564[/C][C]0.325086[/C][/ROW]
[ROW][C]17[/C][C]0.000922[/C][C]0.0063[/C][C]0.497493[/C][/ROW]
[ROW][C]18[/C][C]0.123298[/C][C]0.8453[/C][C]0.201115[/C][/ROW]
[ROW][C]19[/C][C]-0.316521[/C][C]-2.17[/C][C]0.017549[/C][/ROW]
[ROW][C]20[/C][C]0.058361[/C][C]0.4001[/C][C]0.345448[/C][/ROW]
[ROW][C]21[/C][C]0.06328[/C][C]0.4338[/C][C]0.333199[/C][/ROW]
[ROW][C]22[/C][C]-0.029239[/C][C]-0.2005[/C][C]0.420997[/C][/ROW]
[ROW][C]23[/C][C]0.132126[/C][C]0.9058[/C][C]0.184828[/C][/ROW]
[ROW][C]24[/C][C]-0.054021[/C][C]-0.3704[/C][C]0.356392[/C][/ROW]
[ROW][C]25[/C][C]0.076105[/C][C]0.5217[/C][C]0.302148[/C][/ROW]
[ROW][C]26[/C][C]-0.171067[/C][C]-1.1728[/C][C]0.123398[/C][/ROW]
[ROW][C]27[/C][C]0.143922[/C][C]0.9867[/C][C]0.164427[/C][/ROW]
[ROW][C]28[/C][C]-0.214917[/C][C]-1.4734[/C][C]0.073655[/C][/ROW]
[ROW][C]29[/C][C]0.209948[/C][C]1.4393[/C][C]0.078342[/C][/ROW]
[ROW][C]30[/C][C]-0.175042[/C][C]-1.2[/C][C]0.118071[/C][/ROW]
[ROW][C]31[/C][C]0.199522[/C][C]1.3679[/C][C]0.088931[/C][/ROW]
[ROW][C]32[/C][C]-0.00453[/C][C]-0.0311[/C][C]0.487679[/C][/ROW]
[ROW][C]33[/C][C]-0.085245[/C][C]-0.5844[/C][C]0.280871[/C][/ROW]
[ROW][C]34[/C][C]0.029033[/C][C]0.199[/C][C]0.421544[/C][/ROW]
[ROW][C]35[/C][C]-0.115023[/C][C]-0.7886[/C][C]0.217165[/C][/ROW]
[ROW][C]36[/C][C]0.024634[/C][C]0.1689[/C][C]0.433306[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69259&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69259&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
1-0.455275-3.12120.001539
20.2259931.54930.064005
3-0.213269-1.46210.075185
40.031040.21280.416201
5-0.181045-1.24120.11035
60.07390.50660.30739
70.1854091.27110.104974
8-0.133213-0.91330.182883
90.1638931.12360.133446
10-0.241607-1.65640.052154
110.2655361.82040.037533
12-0.382455-2.6220.005872
130.1049160.71930.237769
140.0070270.04820.48089
150.0669350.45890.324216
160.0665790.45640.325086
170.0009220.00630.497493
180.1232980.84530.201115
19-0.316521-2.170.017549
200.0583610.40010.345448
210.063280.43380.333199
22-0.029239-0.20050.420997
230.1321260.90580.184828
24-0.054021-0.37040.356392
250.0761050.52170.302148
26-0.171067-1.17280.123398
270.1439220.98670.164427
28-0.214917-1.47340.073655
290.2099481.43930.078342
30-0.175042-1.20.118071
310.1995221.36790.088931
32-0.00453-0.03110.487679
33-0.085245-0.58440.280871
340.0290330.1990.421544
35-0.115023-0.78860.217165
360.0246340.16890.433306






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.455275-3.12120.001539
20.0236120.16190.436048
3-0.128817-0.88310.190832
4-0.146517-1.00450.160148
5-0.259648-1.78010.040766
6-0.161834-1.10950.136435
70.2198661.50730.06921
8-0.025076-0.17190.432121
90.0323960.22210.4126
10-0.169709-1.16350.125256
110.1849391.26790.105544
12-0.141417-0.96950.168628
13-0.334655-2.29430.013144
14-0.047228-0.32380.373771
150.0507530.34790.364718
160.1369160.93860.176355
17-0.049558-0.33980.367778
180.0676390.46370.322497
19-0.024069-0.1650.434823
20-0.203411-1.39450.084859
210.1998271.36990.088606
22-0.127621-0.87490.193032
230.1521621.04320.151103
24-0.100444-0.68860.247227
25-0.080067-0.54890.292831
260.1241550.85120.199497
270.0610250.41840.338792
28-0.066573-0.45640.325101
29-0.033521-0.22980.409619
300.029480.20210.420354
310.1814011.24360.109902
32-0.103091-0.70680.241603
33-0.0309-0.21180.416575
34-0.066073-0.4530.326326
350.1144060.78430.218391
36-0.097029-0.66520.254588

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.455275 & -3.1212 & 0.001539 \tabularnewline
2 & 0.023612 & 0.1619 & 0.436048 \tabularnewline
3 & -0.128817 & -0.8831 & 0.190832 \tabularnewline
4 & -0.146517 & -1.0045 & 0.160148 \tabularnewline
5 & -0.259648 & -1.7801 & 0.040766 \tabularnewline
6 & -0.161834 & -1.1095 & 0.136435 \tabularnewline
7 & 0.219866 & 1.5073 & 0.06921 \tabularnewline
8 & -0.025076 & -0.1719 & 0.432121 \tabularnewline
9 & 0.032396 & 0.2221 & 0.4126 \tabularnewline
10 & -0.169709 & -1.1635 & 0.125256 \tabularnewline
11 & 0.184939 & 1.2679 & 0.105544 \tabularnewline
12 & -0.141417 & -0.9695 & 0.168628 \tabularnewline
13 & -0.334655 & -2.2943 & 0.013144 \tabularnewline
14 & -0.047228 & -0.3238 & 0.373771 \tabularnewline
15 & 0.050753 & 0.3479 & 0.364718 \tabularnewline
16 & 0.136916 & 0.9386 & 0.176355 \tabularnewline
17 & -0.049558 & -0.3398 & 0.367778 \tabularnewline
18 & 0.067639 & 0.4637 & 0.322497 \tabularnewline
19 & -0.024069 & -0.165 & 0.434823 \tabularnewline
20 & -0.203411 & -1.3945 & 0.084859 \tabularnewline
21 & 0.199827 & 1.3699 & 0.088606 \tabularnewline
22 & -0.127621 & -0.8749 & 0.193032 \tabularnewline
23 & 0.152162 & 1.0432 & 0.151103 \tabularnewline
24 & -0.100444 & -0.6886 & 0.247227 \tabularnewline
25 & -0.080067 & -0.5489 & 0.292831 \tabularnewline
26 & 0.124155 & 0.8512 & 0.199497 \tabularnewline
27 & 0.061025 & 0.4184 & 0.338792 \tabularnewline
28 & -0.066573 & -0.4564 & 0.325101 \tabularnewline
29 & -0.033521 & -0.2298 & 0.409619 \tabularnewline
30 & 0.02948 & 0.2021 & 0.420354 \tabularnewline
31 & 0.181401 & 1.2436 & 0.109902 \tabularnewline
32 & -0.103091 & -0.7068 & 0.241603 \tabularnewline
33 & -0.0309 & -0.2118 & 0.416575 \tabularnewline
34 & -0.066073 & -0.453 & 0.326326 \tabularnewline
35 & 0.114406 & 0.7843 & 0.218391 \tabularnewline
36 & -0.097029 & -0.6652 & 0.254588 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69259&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]-0.455275[/C][C]-3.1212[/C][C]0.001539[/C][/ROW]
[ROW][C]2[/C][C]0.023612[/C][C]0.1619[/C][C]0.436048[/C][/ROW]
[ROW][C]3[/C][C]-0.128817[/C][C]-0.8831[/C][C]0.190832[/C][/ROW]
[ROW][C]4[/C][C]-0.146517[/C][C]-1.0045[/C][C]0.160148[/C][/ROW]
[ROW][C]5[/C][C]-0.259648[/C][C]-1.7801[/C][C]0.040766[/C][/ROW]
[ROW][C]6[/C][C]-0.161834[/C][C]-1.1095[/C][C]0.136435[/C][/ROW]
[ROW][C]7[/C][C]0.219866[/C][C]1.5073[/C][C]0.06921[/C][/ROW]
[ROW][C]8[/C][C]-0.025076[/C][C]-0.1719[/C][C]0.432121[/C][/ROW]
[ROW][C]9[/C][C]0.032396[/C][C]0.2221[/C][C]0.4126[/C][/ROW]
[ROW][C]10[/C][C]-0.169709[/C][C]-1.1635[/C][C]0.125256[/C][/ROW]
[ROW][C]11[/C][C]0.184939[/C][C]1.2679[/C][C]0.105544[/C][/ROW]
[ROW][C]12[/C][C]-0.141417[/C][C]-0.9695[/C][C]0.168628[/C][/ROW]
[ROW][C]13[/C][C]-0.334655[/C][C]-2.2943[/C][C]0.013144[/C][/ROW]
[ROW][C]14[/C][C]-0.047228[/C][C]-0.3238[/C][C]0.373771[/C][/ROW]
[ROW][C]15[/C][C]0.050753[/C][C]0.3479[/C][C]0.364718[/C][/ROW]
[ROW][C]16[/C][C]0.136916[/C][C]0.9386[/C][C]0.176355[/C][/ROW]
[ROW][C]17[/C][C]-0.049558[/C][C]-0.3398[/C][C]0.367778[/C][/ROW]
[ROW][C]18[/C][C]0.067639[/C][C]0.4637[/C][C]0.322497[/C][/ROW]
[ROW][C]19[/C][C]-0.024069[/C][C]-0.165[/C][C]0.434823[/C][/ROW]
[ROW][C]20[/C][C]-0.203411[/C][C]-1.3945[/C][C]0.084859[/C][/ROW]
[ROW][C]21[/C][C]0.199827[/C][C]1.3699[/C][C]0.088606[/C][/ROW]
[ROW][C]22[/C][C]-0.127621[/C][C]-0.8749[/C][C]0.193032[/C][/ROW]
[ROW][C]23[/C][C]0.152162[/C][C]1.0432[/C][C]0.151103[/C][/ROW]
[ROW][C]24[/C][C]-0.100444[/C][C]-0.6886[/C][C]0.247227[/C][/ROW]
[ROW][C]25[/C][C]-0.080067[/C][C]-0.5489[/C][C]0.292831[/C][/ROW]
[ROW][C]26[/C][C]0.124155[/C][C]0.8512[/C][C]0.199497[/C][/ROW]
[ROW][C]27[/C][C]0.061025[/C][C]0.4184[/C][C]0.338792[/C][/ROW]
[ROW][C]28[/C][C]-0.066573[/C][C]-0.4564[/C][C]0.325101[/C][/ROW]
[ROW][C]29[/C][C]-0.033521[/C][C]-0.2298[/C][C]0.409619[/C][/ROW]
[ROW][C]30[/C][C]0.02948[/C][C]0.2021[/C][C]0.420354[/C][/ROW]
[ROW][C]31[/C][C]0.181401[/C][C]1.2436[/C][C]0.109902[/C][/ROW]
[ROW][C]32[/C][C]-0.103091[/C][C]-0.7068[/C][C]0.241603[/C][/ROW]
[ROW][C]33[/C][C]-0.0309[/C][C]-0.2118[/C][C]0.416575[/C][/ROW]
[ROW][C]34[/C][C]-0.066073[/C][C]-0.453[/C][C]0.326326[/C][/ROW]
[ROW][C]35[/C][C]0.114406[/C][C]0.7843[/C][C]0.218391[/C][/ROW]
[ROW][C]36[/C][C]-0.097029[/C][C]-0.6652[/C][C]0.254588[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69259&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69259&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
1-0.455275-3.12120.001539
20.0236120.16190.436048
3-0.128817-0.88310.190832
4-0.146517-1.00450.160148
5-0.259648-1.78010.040766
6-0.161834-1.10950.136435
70.2198661.50730.06921
8-0.025076-0.17190.432121
90.0323960.22210.4126
10-0.169709-1.16350.125256
110.1849391.26790.105544
12-0.141417-0.96950.168628
13-0.334655-2.29430.013144
14-0.047228-0.32380.373771
150.0507530.34790.364718
160.1369160.93860.176355
17-0.049558-0.33980.367778
180.0676390.46370.322497
19-0.024069-0.1650.434823
20-0.203411-1.39450.084859
210.1998271.36990.088606
22-0.127621-0.87490.193032
230.1521621.04320.151103
24-0.100444-0.68860.247227
25-0.080067-0.54890.292831
260.1241550.85120.199497
270.0610250.41840.338792
28-0.066573-0.45640.325101
29-0.033521-0.22980.409619
300.029480.20210.420354
310.1814011.24360.109902
32-0.103091-0.70680.241603
33-0.0309-0.21180.416575
34-0.066073-0.4530.326326
350.1144060.78430.218391
36-0.097029-0.66520.254588


Figures (Output of Computation)

Input Parameters & R Code

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