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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 12:44:23 -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/t1259351159su4ijt9mw55d5s8.htm/, Retrieved Sun, 28 Apr 2024 20:29:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61187, Retrieved Sun, 28 Apr 2024 20:29:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [WS 8.3] [2009-11-27 19:44:23] [71c065898bd1c08eef04509b4bcee039] [Current]
-   P             [(Partial) Autocorrelation Function] [Workshop 8] [2009-12-03 22:29:45] [786e067c4f7cec17385c4742b96b6dfa]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.00
94.97
107.50
124.27
107.06
79.71
163.41
144.83
166.82
154.26
132.60
157.51
104.02
106.03
113.23
117.64
113.34
66.62
185.99
174.57
208.19
163.81
162.46
148.16
113.41
105.63
111.79
132.36
110.75
67.37
178.29
156.38
189.71
152.80
150.80
160.40
127.25
108.47
117.09
147.25
116.19
75.83
181.94
179.12
183.15
197.90
155.42
162.54
125.90
105.50
121.11
137.51
97.20
69.74
152.58
146.59
161.16
152.84
121.95
140.12

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=61187&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=61187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61187&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
1-0.59235-4.06099.2e-05
20.3111552.13320.019081
3-0.139808-0.95850.171363
4-0.018583-0.12740.449585
5-0.095314-0.65340.258328
60.1272330.87230.19375
7-0.106639-0.73110.23418
80.1334320.91480.182492
9-0.050074-0.34330.366456
10-0.002578-0.01770.492988
110.0773070.530.299307
12-0.227933-1.56260.062424
130.0279730.19180.424372
140.0036220.02480.490146
15-0.010799-0.0740.470649
160.0539740.370.356513
170.0254070.17420.431236
180.0014620.010.496022
19-0.023842-0.16350.435431
20-0.091485-0.62720.266786
210.2138761.46630.074618
22-0.344638-2.36270.011166
230.3394042.32680.012167
24-0.195863-1.34280.092898
250.1423430.97590.167066
26-0.022573-0.15480.43884
270.1141940.78290.218815
28-0.212839-1.45920.075588
290.1600441.09720.139071
30-0.141257-0.96840.168899
310.0800760.5490.292811
320.0318380.21830.414083
33-0.075659-0.51870.303204
340.0798080.54710.293436
35-0.060795-0.41680.339365
36-0.030836-0.21140.416745

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.59235 & -4.0609 & 9.2e-05 \tabularnewline
2 & 0.311155 & 2.1332 & 0.019081 \tabularnewline
3 & -0.139808 & -0.9585 & 0.171363 \tabularnewline
4 & -0.018583 & -0.1274 & 0.449585 \tabularnewline
5 & -0.095314 & -0.6534 & 0.258328 \tabularnewline
6 & 0.127233 & 0.8723 & 0.19375 \tabularnewline
7 & -0.106639 & -0.7311 & 0.23418 \tabularnewline
8 & 0.133432 & 0.9148 & 0.182492 \tabularnewline
9 & -0.050074 & -0.3433 & 0.366456 \tabularnewline
10 & -0.002578 & -0.0177 & 0.492988 \tabularnewline
11 & 0.077307 & 0.53 & 0.299307 \tabularnewline
12 & -0.227933 & -1.5626 & 0.062424 \tabularnewline
13 & 0.027973 & 0.1918 & 0.424372 \tabularnewline
14 & 0.003622 & 0.0248 & 0.490146 \tabularnewline
15 & -0.010799 & -0.074 & 0.470649 \tabularnewline
16 & 0.053974 & 0.37 & 0.356513 \tabularnewline
17 & 0.025407 & 0.1742 & 0.431236 \tabularnewline
18 & 0.001462 & 0.01 & 0.496022 \tabularnewline
19 & -0.023842 & -0.1635 & 0.435431 \tabularnewline
20 & -0.091485 & -0.6272 & 0.266786 \tabularnewline
21 & 0.213876 & 1.4663 & 0.074618 \tabularnewline
22 & -0.344638 & -2.3627 & 0.011166 \tabularnewline
23 & 0.339404 & 2.3268 & 0.012167 \tabularnewline
24 & -0.195863 & -1.3428 & 0.092898 \tabularnewline
25 & 0.142343 & 0.9759 & 0.167066 \tabularnewline
26 & -0.022573 & -0.1548 & 0.43884 \tabularnewline
27 & 0.114194 & 0.7829 & 0.218815 \tabularnewline
28 & -0.212839 & -1.4592 & 0.075588 \tabularnewline
29 & 0.160044 & 1.0972 & 0.139071 \tabularnewline
30 & -0.141257 & -0.9684 & 0.168899 \tabularnewline
31 & 0.080076 & 0.549 & 0.292811 \tabularnewline
32 & 0.031838 & 0.2183 & 0.414083 \tabularnewline
33 & -0.075659 & -0.5187 & 0.303204 \tabularnewline
34 & 0.079808 & 0.5471 & 0.293436 \tabularnewline
35 & -0.060795 & -0.4168 & 0.339365 \tabularnewline
36 & -0.030836 & -0.2114 & 0.416745 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61187&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]-0.59235[/C][C]-4.0609[/C][C]9.2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.311155[/C][C]2.1332[/C][C]0.019081[/C][/ROW]
[ROW][C]3[/C][C]-0.139808[/C][C]-0.9585[/C][C]0.171363[/C][/ROW]
[ROW][C]4[/C][C]-0.018583[/C][C]-0.1274[/C][C]0.449585[/C][/ROW]
[ROW][C]5[/C][C]-0.095314[/C][C]-0.6534[/C][C]0.258328[/C][/ROW]
[ROW][C]6[/C][C]0.127233[/C][C]0.8723[/C][C]0.19375[/C][/ROW]
[ROW][C]7[/C][C]-0.106639[/C][C]-0.7311[/C][C]0.23418[/C][/ROW]
[ROW][C]8[/C][C]0.133432[/C][C]0.9148[/C][C]0.182492[/C][/ROW]
[ROW][C]9[/C][C]-0.050074[/C][C]-0.3433[/C][C]0.366456[/C][/ROW]
[ROW][C]10[/C][C]-0.002578[/C][C]-0.0177[/C][C]0.492988[/C][/ROW]
[ROW][C]11[/C][C]0.077307[/C][C]0.53[/C][C]0.299307[/C][/ROW]
[ROW][C]12[/C][C]-0.227933[/C][C]-1.5626[/C][C]0.062424[/C][/ROW]
[ROW][C]13[/C][C]0.027973[/C][C]0.1918[/C][C]0.424372[/C][/ROW]
[ROW][C]14[/C][C]0.003622[/C][C]0.0248[/C][C]0.490146[/C][/ROW]
[ROW][C]15[/C][C]-0.010799[/C][C]-0.074[/C][C]0.470649[/C][/ROW]
[ROW][C]16[/C][C]0.053974[/C][C]0.37[/C][C]0.356513[/C][/ROW]
[ROW][C]17[/C][C]0.025407[/C][C]0.1742[/C][C]0.431236[/C][/ROW]
[ROW][C]18[/C][C]0.001462[/C][C]0.01[/C][C]0.496022[/C][/ROW]
[ROW][C]19[/C][C]-0.023842[/C][C]-0.1635[/C][C]0.435431[/C][/ROW]
[ROW][C]20[/C][C]-0.091485[/C][C]-0.6272[/C][C]0.266786[/C][/ROW]
[ROW][C]21[/C][C]0.213876[/C][C]1.4663[/C][C]0.074618[/C][/ROW]
[ROW][C]22[/C][C]-0.344638[/C][C]-2.3627[/C][C]0.011166[/C][/ROW]
[ROW][C]23[/C][C]0.339404[/C][C]2.3268[/C][C]0.012167[/C][/ROW]
[ROW][C]24[/C][C]-0.195863[/C][C]-1.3428[/C][C]0.092898[/C][/ROW]
[ROW][C]25[/C][C]0.142343[/C][C]0.9759[/C][C]0.167066[/C][/ROW]
[ROW][C]26[/C][C]-0.022573[/C][C]-0.1548[/C][C]0.43884[/C][/ROW]
[ROW][C]27[/C][C]0.114194[/C][C]0.7829[/C][C]0.218815[/C][/ROW]
[ROW][C]28[/C][C]-0.212839[/C][C]-1.4592[/C][C]0.075588[/C][/ROW]
[ROW][C]29[/C][C]0.160044[/C][C]1.0972[/C][C]0.139071[/C][/ROW]
[ROW][C]30[/C][C]-0.141257[/C][C]-0.9684[/C][C]0.168899[/C][/ROW]
[ROW][C]31[/C][C]0.080076[/C][C]0.549[/C][C]0.292811[/C][/ROW]
[ROW][C]32[/C][C]0.031838[/C][C]0.2183[/C][C]0.414083[/C][/ROW]
[ROW][C]33[/C][C]-0.075659[/C][C]-0.5187[/C][C]0.303204[/C][/ROW]
[ROW][C]34[/C][C]0.079808[/C][C]0.5471[/C][C]0.293436[/C][/ROW]
[ROW][C]35[/C][C]-0.060795[/C][C]-0.4168[/C][C]0.339365[/C][/ROW]
[ROW][C]36[/C][C]-0.030836[/C][C]-0.2114[/C][C]0.416745[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61187&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
1-0.59235-4.06099.2e-05
20.3111552.13320.019081
3-0.139808-0.95850.171363
4-0.018583-0.12740.449585
5-0.095314-0.65340.258328
60.1272330.87230.19375
7-0.106639-0.73110.23418
80.1334320.91480.182492
9-0.050074-0.34330.366456
10-0.002578-0.01770.492988
110.0773070.530.299307
12-0.227933-1.56260.062424
130.0279730.19180.424372
140.0036220.02480.490146
15-0.010799-0.0740.470649
160.0539740.370.356513
170.0254070.17420.431236
180.0014620.010.496022
19-0.023842-0.16350.435431
20-0.091485-0.62720.266786
210.2138761.46630.074618
22-0.344638-2.36270.011166
230.3394042.32680.012167
24-0.195863-1.34280.092898
250.1423430.97590.167066
26-0.022573-0.15480.43884
270.1141940.78290.218815
28-0.212839-1.45920.075588
290.1600441.09720.139071
30-0.141257-0.96840.168899
310.0800760.5490.292811
320.0318380.21830.414083
33-0.075659-0.51870.303204
340.0798080.54710.293436
35-0.060795-0.41680.339365
36-0.030836-0.21140.416745






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.59235-4.06099.2e-05
2-0.061196-0.41950.338368
30.0302060.20710.418419
4-0.116362-0.79770.214517
5-0.265343-1.81910.037635
6-0.022674-0.15540.438567
70.007250.04970.480285
80.0529630.36310.359079
90.0373050.25580.399629
10-0.034259-0.23490.407667
110.118190.81030.210935
12-0.184518-1.2650.106055
13-0.343455-2.35460.011385
14-0.162347-1.1130.135685
15-0.008414-0.05770.477123
16-0.02992-0.20510.419181
17-0.113677-0.77930.219846
18-0.002756-0.01890.492502
190.0236670.16230.435902
20-0.181605-1.2450.109648
210.1917221.31440.097549
22-0.190291-1.30460.099195
23-0.004293-0.02940.488323
24-0.036233-0.24840.402454
25-0.109742-0.75240.227795
260.0151080.10360.458972
270.2009141.37740.087457
28-0.021437-0.1470.441895
29-0.113918-0.7810.219364
300.0801230.54930.292702
310.0552620.37890.35325
32-0.015458-0.1060.458025
330.0054970.03770.48505
34-0.088482-0.60660.273518
35-0.066113-0.45320.326229
36-0.027281-0.1870.42622

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.59235 & -4.0609 & 9.2e-05 \tabularnewline
2 & -0.061196 & -0.4195 & 0.338368 \tabularnewline
3 & 0.030206 & 0.2071 & 0.418419 \tabularnewline
4 & -0.116362 & -0.7977 & 0.214517 \tabularnewline
5 & -0.265343 & -1.8191 & 0.037635 \tabularnewline
6 & -0.022674 & -0.1554 & 0.438567 \tabularnewline
7 & 0.00725 & 0.0497 & 0.480285 \tabularnewline
8 & 0.052963 & 0.3631 & 0.359079 \tabularnewline
9 & 0.037305 & 0.2558 & 0.399629 \tabularnewline
10 & -0.034259 & -0.2349 & 0.407667 \tabularnewline
11 & 0.11819 & 0.8103 & 0.210935 \tabularnewline
12 & -0.184518 & -1.265 & 0.106055 \tabularnewline
13 & -0.343455 & -2.3546 & 0.011385 \tabularnewline
14 & -0.162347 & -1.113 & 0.135685 \tabularnewline
15 & -0.008414 & -0.0577 & 0.477123 \tabularnewline
16 & -0.02992 & -0.2051 & 0.419181 \tabularnewline
17 & -0.113677 & -0.7793 & 0.219846 \tabularnewline
18 & -0.002756 & -0.0189 & 0.492502 \tabularnewline
19 & 0.023667 & 0.1623 & 0.435902 \tabularnewline
20 & -0.181605 & -1.245 & 0.109648 \tabularnewline
21 & 0.191722 & 1.3144 & 0.097549 \tabularnewline
22 & -0.190291 & -1.3046 & 0.099195 \tabularnewline
23 & -0.004293 & -0.0294 & 0.488323 \tabularnewline
24 & -0.036233 & -0.2484 & 0.402454 \tabularnewline
25 & -0.109742 & -0.7524 & 0.227795 \tabularnewline
26 & 0.015108 & 0.1036 & 0.458972 \tabularnewline
27 & 0.200914 & 1.3774 & 0.087457 \tabularnewline
28 & -0.021437 & -0.147 & 0.441895 \tabularnewline
29 & -0.113918 & -0.781 & 0.219364 \tabularnewline
30 & 0.080123 & 0.5493 & 0.292702 \tabularnewline
31 & 0.055262 & 0.3789 & 0.35325 \tabularnewline
32 & -0.015458 & -0.106 & 0.458025 \tabularnewline
33 & 0.005497 & 0.0377 & 0.48505 \tabularnewline
34 & -0.088482 & -0.6066 & 0.273518 \tabularnewline
35 & -0.066113 & -0.4532 & 0.326229 \tabularnewline
36 & -0.027281 & -0.187 & 0.42622 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61187&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]-0.59235[/C][C]-4.0609[/C][C]9.2e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.061196[/C][C]-0.4195[/C][C]0.338368[/C][/ROW]
[ROW][C]3[/C][C]0.030206[/C][C]0.2071[/C][C]0.418419[/C][/ROW]
[ROW][C]4[/C][C]-0.116362[/C][C]-0.7977[/C][C]0.214517[/C][/ROW]
[ROW][C]5[/C][C]-0.265343[/C][C]-1.8191[/C][C]0.037635[/C][/ROW]
[ROW][C]6[/C][C]-0.022674[/C][C]-0.1554[/C][C]0.438567[/C][/ROW]
[ROW][C]7[/C][C]0.00725[/C][C]0.0497[/C][C]0.480285[/C][/ROW]
[ROW][C]8[/C][C]0.052963[/C][C]0.3631[/C][C]0.359079[/C][/ROW]
[ROW][C]9[/C][C]0.037305[/C][C]0.2558[/C][C]0.399629[/C][/ROW]
[ROW][C]10[/C][C]-0.034259[/C][C]-0.2349[/C][C]0.407667[/C][/ROW]
[ROW][C]11[/C][C]0.11819[/C][C]0.8103[/C][C]0.210935[/C][/ROW]
[ROW][C]12[/C][C]-0.184518[/C][C]-1.265[/C][C]0.106055[/C][/ROW]
[ROW][C]13[/C][C]-0.343455[/C][C]-2.3546[/C][C]0.011385[/C][/ROW]
[ROW][C]14[/C][C]-0.162347[/C][C]-1.113[/C][C]0.135685[/C][/ROW]
[ROW][C]15[/C][C]-0.008414[/C][C]-0.0577[/C][C]0.477123[/C][/ROW]
[ROW][C]16[/C][C]-0.02992[/C][C]-0.2051[/C][C]0.419181[/C][/ROW]
[ROW][C]17[/C][C]-0.113677[/C][C]-0.7793[/C][C]0.219846[/C][/ROW]
[ROW][C]18[/C][C]-0.002756[/C][C]-0.0189[/C][C]0.492502[/C][/ROW]
[ROW][C]19[/C][C]0.023667[/C][C]0.1623[/C][C]0.435902[/C][/ROW]
[ROW][C]20[/C][C]-0.181605[/C][C]-1.245[/C][C]0.109648[/C][/ROW]
[ROW][C]21[/C][C]0.191722[/C][C]1.3144[/C][C]0.097549[/C][/ROW]
[ROW][C]22[/C][C]-0.190291[/C][C]-1.3046[/C][C]0.099195[/C][/ROW]
[ROW][C]23[/C][C]-0.004293[/C][C]-0.0294[/C][C]0.488323[/C][/ROW]
[ROW][C]24[/C][C]-0.036233[/C][C]-0.2484[/C][C]0.402454[/C][/ROW]
[ROW][C]25[/C][C]-0.109742[/C][C]-0.7524[/C][C]0.227795[/C][/ROW]
[ROW][C]26[/C][C]0.015108[/C][C]0.1036[/C][C]0.458972[/C][/ROW]
[ROW][C]27[/C][C]0.200914[/C][C]1.3774[/C][C]0.087457[/C][/ROW]
[ROW][C]28[/C][C]-0.021437[/C][C]-0.147[/C][C]0.441895[/C][/ROW]
[ROW][C]29[/C][C]-0.113918[/C][C]-0.781[/C][C]0.219364[/C][/ROW]
[ROW][C]30[/C][C]0.080123[/C][C]0.5493[/C][C]0.292702[/C][/ROW]
[ROW][C]31[/C][C]0.055262[/C][C]0.3789[/C][C]0.35325[/C][/ROW]
[ROW][C]32[/C][C]-0.015458[/C][C]-0.106[/C][C]0.458025[/C][/ROW]
[ROW][C]33[/C][C]0.005497[/C][C]0.0377[/C][C]0.48505[/C][/ROW]
[ROW][C]34[/C][C]-0.088482[/C][C]-0.6066[/C][C]0.273518[/C][/ROW]
[ROW][C]35[/C][C]-0.066113[/C][C]-0.4532[/C][C]0.326229[/C][/ROW]
[ROW][C]36[/C][C]-0.027281[/C][C]-0.187[/C][C]0.42622[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61187&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
1-0.59235-4.06099.2e-05
2-0.061196-0.41950.338368
30.0302060.20710.418419
4-0.116362-0.79770.214517
5-0.265343-1.81910.037635
6-0.022674-0.15540.438567
70.007250.04970.480285
80.0529630.36310.359079
90.0373050.25580.399629
10-0.034259-0.23490.407667
110.118190.81030.210935
12-0.184518-1.2650.106055
13-0.343455-2.35460.011385
14-0.162347-1.1130.135685
15-0.008414-0.05770.477123
16-0.02992-0.20510.419181
17-0.113677-0.77930.219846
18-0.002756-0.01890.492502
190.0236670.16230.435902
20-0.181605-1.2450.109648
210.1917221.31440.097549
22-0.190291-1.30460.099195
23-0.004293-0.02940.488323
24-0.036233-0.24840.402454
25-0.109742-0.75240.227795
260.0151080.10360.458972
270.2009141.37740.087457
28-0.021437-0.1470.441895
29-0.113918-0.7810.219364
300.0801230.54930.292702
310.0552620.37890.35325
32-0.015458-0.1060.458025
330.0054970.03770.48505
34-0.088482-0.60660.273518
35-0.066113-0.45320.326229
36-0.027281-0.1870.42622


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')