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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, 11 Dec 2009 05:11:05 -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/11/t12605335297rxy5mk84y0cyir.htm/, Retrieved Sun, 28 Apr 2024 21:42:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66060, Retrieved Sun, 28 Apr 2024 21:42:41 +0000
QR Codes:

Original text written by user:Paper: ACF: Amerikaanse inflatie
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102

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]
-    D        [(Partial) Autocorrelation Function] [Shw8: Method 1 AC...] [2009-11-27 10:59:38] [3c8b83428ce260cd44df892bb7619588]
-    D            [(Partial) Autocorrelation Function] [Paper: ACF: Ameri...] [2009-12-11 12:11:05] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.527
0.472
0.000
0.052
0.313
0.364
0.363
-0.155
0.052
0.568
0.668
1.378
0.252
-0.402
-0.050
0.555
0.050
0.150
0.450
0.299
0.199
0.496
0.444
-0.393
-0.444
0.198
0.494
0.133
0.388
0.484
0.278
0.369
0.165
0.155
0.087
0.414
0.360
0.975
0.270
0.359
0.169
0.381
0.154
0.486
0.925
0.728
-0.014
0.046
-0.819
-1.674
-0.788
0.279
0.396
-0.141
-0.019
0.099
0.742
0.005
0.448

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=66060&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=66060&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66060&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
10.467083.58770.000339
20.0070760.05430.47842
3-0.11682-0.89730.1866
4-0.058928-0.45260.326235
5-0.132417-1.01710.156625
6-0.04899-0.37630.354022
70.0042370.03250.487075
8-0.031642-0.2430.404406
9-0.055397-0.42550.336004
100.045870.35230.362921
110.0403110.30960.378964
12-0.217543-1.6710.050011
13-0.243178-1.86790.033373
14-0.089983-0.69120.246084
150.0610020.46860.320554
160.0402680.30930.379089
170.0334390.25690.399094
18-0.02435-0.1870.426138
19-0.006754-0.05190.479401
20-0.081599-0.62680.266613
21-0.054112-0.41560.33959
22-0.023549-0.18090.428541
23-0.055068-0.4230.336922
24-0.003361-0.02580.489744
250.1794111.37810.086691
260.2346511.80240.038296
270.0262790.20190.420363
28-0.059318-0.45560.325165
29-0.017538-0.13470.44665
300.0141930.1090.45678
31-0.068196-0.52380.301181
32-0.015892-0.12210.451628
330.0753130.57850.282568
340.0681450.52340.301316
350.0658560.50590.307422
360.1022120.78510.217766

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.46708 & 3.5877 & 0.000339 \tabularnewline
2 & 0.007076 & 0.0543 & 0.47842 \tabularnewline
3 & -0.11682 & -0.8973 & 0.1866 \tabularnewline
4 & -0.058928 & -0.4526 & 0.326235 \tabularnewline
5 & -0.132417 & -1.0171 & 0.156625 \tabularnewline
6 & -0.04899 & -0.3763 & 0.354022 \tabularnewline
7 & 0.004237 & 0.0325 & 0.487075 \tabularnewline
8 & -0.031642 & -0.243 & 0.404406 \tabularnewline
9 & -0.055397 & -0.4255 & 0.336004 \tabularnewline
10 & 0.04587 & 0.3523 & 0.362921 \tabularnewline
11 & 0.040311 & 0.3096 & 0.378964 \tabularnewline
12 & -0.217543 & -1.671 & 0.050011 \tabularnewline
13 & -0.243178 & -1.8679 & 0.033373 \tabularnewline
14 & -0.089983 & -0.6912 & 0.246084 \tabularnewline
15 & 0.061002 & 0.4686 & 0.320554 \tabularnewline
16 & 0.040268 & 0.3093 & 0.379089 \tabularnewline
17 & 0.033439 & 0.2569 & 0.399094 \tabularnewline
18 & -0.02435 & -0.187 & 0.426138 \tabularnewline
19 & -0.006754 & -0.0519 & 0.479401 \tabularnewline
20 & -0.081599 & -0.6268 & 0.266613 \tabularnewline
21 & -0.054112 & -0.4156 & 0.33959 \tabularnewline
22 & -0.023549 & -0.1809 & 0.428541 \tabularnewline
23 & -0.055068 & -0.423 & 0.336922 \tabularnewline
24 & -0.003361 & -0.0258 & 0.489744 \tabularnewline
25 & 0.179411 & 1.3781 & 0.086691 \tabularnewline
26 & 0.234651 & 1.8024 & 0.038296 \tabularnewline
27 & 0.026279 & 0.2019 & 0.420363 \tabularnewline
28 & -0.059318 & -0.4556 & 0.325165 \tabularnewline
29 & -0.017538 & -0.1347 & 0.44665 \tabularnewline
30 & 0.014193 & 0.109 & 0.45678 \tabularnewline
31 & -0.068196 & -0.5238 & 0.301181 \tabularnewline
32 & -0.015892 & -0.1221 & 0.451628 \tabularnewline
33 & 0.075313 & 0.5785 & 0.282568 \tabularnewline
34 & 0.068145 & 0.5234 & 0.301316 \tabularnewline
35 & 0.065856 & 0.5059 & 0.307422 \tabularnewline
36 & 0.102212 & 0.7851 & 0.217766 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66060&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]0.46708[/C][C]3.5877[/C][C]0.000339[/C][/ROW]
[ROW][C]2[/C][C]0.007076[/C][C]0.0543[/C][C]0.47842[/C][/ROW]
[ROW][C]3[/C][C]-0.11682[/C][C]-0.8973[/C][C]0.1866[/C][/ROW]
[ROW][C]4[/C][C]-0.058928[/C][C]-0.4526[/C][C]0.326235[/C][/ROW]
[ROW][C]5[/C][C]-0.132417[/C][C]-1.0171[/C][C]0.156625[/C][/ROW]
[ROW][C]6[/C][C]-0.04899[/C][C]-0.3763[/C][C]0.354022[/C][/ROW]
[ROW][C]7[/C][C]0.004237[/C][C]0.0325[/C][C]0.487075[/C][/ROW]
[ROW][C]8[/C][C]-0.031642[/C][C]-0.243[/C][C]0.404406[/C][/ROW]
[ROW][C]9[/C][C]-0.055397[/C][C]-0.4255[/C][C]0.336004[/C][/ROW]
[ROW][C]10[/C][C]0.04587[/C][C]0.3523[/C][C]0.362921[/C][/ROW]
[ROW][C]11[/C][C]0.040311[/C][C]0.3096[/C][C]0.378964[/C][/ROW]
[ROW][C]12[/C][C]-0.217543[/C][C]-1.671[/C][C]0.050011[/C][/ROW]
[ROW][C]13[/C][C]-0.243178[/C][C]-1.8679[/C][C]0.033373[/C][/ROW]
[ROW][C]14[/C][C]-0.089983[/C][C]-0.6912[/C][C]0.246084[/C][/ROW]
[ROW][C]15[/C][C]0.061002[/C][C]0.4686[/C][C]0.320554[/C][/ROW]
[ROW][C]16[/C][C]0.040268[/C][C]0.3093[/C][C]0.379089[/C][/ROW]
[ROW][C]17[/C][C]0.033439[/C][C]0.2569[/C][C]0.399094[/C][/ROW]
[ROW][C]18[/C][C]-0.02435[/C][C]-0.187[/C][C]0.426138[/C][/ROW]
[ROW][C]19[/C][C]-0.006754[/C][C]-0.0519[/C][C]0.479401[/C][/ROW]
[ROW][C]20[/C][C]-0.081599[/C][C]-0.6268[/C][C]0.266613[/C][/ROW]
[ROW][C]21[/C][C]-0.054112[/C][C]-0.4156[/C][C]0.33959[/C][/ROW]
[ROW][C]22[/C][C]-0.023549[/C][C]-0.1809[/C][C]0.428541[/C][/ROW]
[ROW][C]23[/C][C]-0.055068[/C][C]-0.423[/C][C]0.336922[/C][/ROW]
[ROW][C]24[/C][C]-0.003361[/C][C]-0.0258[/C][C]0.489744[/C][/ROW]
[ROW][C]25[/C][C]0.179411[/C][C]1.3781[/C][C]0.086691[/C][/ROW]
[ROW][C]26[/C][C]0.234651[/C][C]1.8024[/C][C]0.038296[/C][/ROW]
[ROW][C]27[/C][C]0.026279[/C][C]0.2019[/C][C]0.420363[/C][/ROW]
[ROW][C]28[/C][C]-0.059318[/C][C]-0.4556[/C][C]0.325165[/C][/ROW]
[ROW][C]29[/C][C]-0.017538[/C][C]-0.1347[/C][C]0.44665[/C][/ROW]
[ROW][C]30[/C][C]0.014193[/C][C]0.109[/C][C]0.45678[/C][/ROW]
[ROW][C]31[/C][C]-0.068196[/C][C]-0.5238[/C][C]0.301181[/C][/ROW]
[ROW][C]32[/C][C]-0.015892[/C][C]-0.1221[/C][C]0.451628[/C][/ROW]
[ROW][C]33[/C][C]0.075313[/C][C]0.5785[/C][C]0.282568[/C][/ROW]
[ROW][C]34[/C][C]0.068145[/C][C]0.5234[/C][C]0.301316[/C][/ROW]
[ROW][C]35[/C][C]0.065856[/C][C]0.5059[/C][C]0.307422[/C][/ROW]
[ROW][C]36[/C][C]0.102212[/C][C]0.7851[/C][C]0.217766[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66060&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66060&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
10.467083.58770.000339
20.0070760.05430.47842
3-0.11682-0.89730.1866
4-0.058928-0.45260.326235
5-0.132417-1.01710.156625
6-0.04899-0.37630.354022
70.0042370.03250.487075
8-0.031642-0.2430.404406
9-0.055397-0.42550.336004
100.045870.35230.362921
110.0403110.30960.378964
12-0.217543-1.6710.050011
13-0.243178-1.86790.033373
14-0.089983-0.69120.246084
150.0610020.46860.320554
160.0402680.30930.379089
170.0334390.25690.399094
18-0.02435-0.1870.426138
19-0.006754-0.05190.479401
20-0.081599-0.62680.266613
21-0.054112-0.41560.33959
22-0.023549-0.18090.428541
23-0.055068-0.4230.336922
24-0.003361-0.02580.489744
250.1794111.37810.086691
260.2346511.80240.038296
270.0262790.20190.420363
28-0.059318-0.45560.325165
29-0.017538-0.13470.44665
300.0141930.1090.45678
31-0.068196-0.52380.301181
32-0.015892-0.12210.451628
330.0753130.57850.282568
340.0681450.52340.301316
350.0658560.50590.307422
360.1022120.78510.217766






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.467083.58770.000339
2-0.26999-2.07380.021234
30.0070220.05390.478583
40.0127610.0980.461124
5-0.18619-1.43020.078974
60.1347891.03530.152369
7-0.070321-0.54010.295566
8-0.067825-0.5210.302169
90.0273260.20990.417236
100.0534410.41050.341467
11-0.051181-0.39310.347819
12-0.302283-2.32190.011856
130.0540650.41530.33972
14-0.032223-0.24750.402685
150.0508720.39080.348692
16-0.032827-0.25210.400901
17-0.060645-0.46580.321529
18-0.036186-0.27790.391011
190.0552040.4240.336543
20-0.16807-1.2910.100874
210.0005190.0040.498416
220.014260.10950.456577
23-0.096403-0.74050.230971
240.0746060.57310.28439
250.1042330.80060.213279
260.0295820.22720.410517
27-0.120027-0.92190.180156
280.0777810.59740.276248
290.0080740.0620.475379
30-0.040987-0.31480.377002
31-0.015666-0.12030.452313
32-0.023313-0.17910.429246
330.1041990.80040.213354
340.0058590.0450.482129
350.0535080.4110.341281
36-0.009338-0.07170.471532

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.46708 & 3.5877 & 0.000339 \tabularnewline
2 & -0.26999 & -2.0738 & 0.021234 \tabularnewline
3 & 0.007022 & 0.0539 & 0.478583 \tabularnewline
4 & 0.012761 & 0.098 & 0.461124 \tabularnewline
5 & -0.18619 & -1.4302 & 0.078974 \tabularnewline
6 & 0.134789 & 1.0353 & 0.152369 \tabularnewline
7 & -0.070321 & -0.5401 & 0.295566 \tabularnewline
8 & -0.067825 & -0.521 & 0.302169 \tabularnewline
9 & 0.027326 & 0.2099 & 0.417236 \tabularnewline
10 & 0.053441 & 0.4105 & 0.341467 \tabularnewline
11 & -0.051181 & -0.3931 & 0.347819 \tabularnewline
12 & -0.302283 & -2.3219 & 0.011856 \tabularnewline
13 & 0.054065 & 0.4153 & 0.33972 \tabularnewline
14 & -0.032223 & -0.2475 & 0.402685 \tabularnewline
15 & 0.050872 & 0.3908 & 0.348692 \tabularnewline
16 & -0.032827 & -0.2521 & 0.400901 \tabularnewline
17 & -0.060645 & -0.4658 & 0.321529 \tabularnewline
18 & -0.036186 & -0.2779 & 0.391011 \tabularnewline
19 & 0.055204 & 0.424 & 0.336543 \tabularnewline
20 & -0.16807 & -1.291 & 0.100874 \tabularnewline
21 & 0.000519 & 0.004 & 0.498416 \tabularnewline
22 & 0.01426 & 0.1095 & 0.456577 \tabularnewline
23 & -0.096403 & -0.7405 & 0.230971 \tabularnewline
24 & 0.074606 & 0.5731 & 0.28439 \tabularnewline
25 & 0.104233 & 0.8006 & 0.213279 \tabularnewline
26 & 0.029582 & 0.2272 & 0.410517 \tabularnewline
27 & -0.120027 & -0.9219 & 0.180156 \tabularnewline
28 & 0.077781 & 0.5974 & 0.276248 \tabularnewline
29 & 0.008074 & 0.062 & 0.475379 \tabularnewline
30 & -0.040987 & -0.3148 & 0.377002 \tabularnewline
31 & -0.015666 & -0.1203 & 0.452313 \tabularnewline
32 & -0.023313 & -0.1791 & 0.429246 \tabularnewline
33 & 0.104199 & 0.8004 & 0.213354 \tabularnewline
34 & 0.005859 & 0.045 & 0.482129 \tabularnewline
35 & 0.053508 & 0.411 & 0.341281 \tabularnewline
36 & -0.009338 & -0.0717 & 0.471532 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66060&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]0.46708[/C][C]3.5877[/C][C]0.000339[/C][/ROW]
[ROW][C]2[/C][C]-0.26999[/C][C]-2.0738[/C][C]0.021234[/C][/ROW]
[ROW][C]3[/C][C]0.007022[/C][C]0.0539[/C][C]0.478583[/C][/ROW]
[ROW][C]4[/C][C]0.012761[/C][C]0.098[/C][C]0.461124[/C][/ROW]
[ROW][C]5[/C][C]-0.18619[/C][C]-1.4302[/C][C]0.078974[/C][/ROW]
[ROW][C]6[/C][C]0.134789[/C][C]1.0353[/C][C]0.152369[/C][/ROW]
[ROW][C]7[/C][C]-0.070321[/C][C]-0.5401[/C][C]0.295566[/C][/ROW]
[ROW][C]8[/C][C]-0.067825[/C][C]-0.521[/C][C]0.302169[/C][/ROW]
[ROW][C]9[/C][C]0.027326[/C][C]0.2099[/C][C]0.417236[/C][/ROW]
[ROW][C]10[/C][C]0.053441[/C][C]0.4105[/C][C]0.341467[/C][/ROW]
[ROW][C]11[/C][C]-0.051181[/C][C]-0.3931[/C][C]0.347819[/C][/ROW]
[ROW][C]12[/C][C]-0.302283[/C][C]-2.3219[/C][C]0.011856[/C][/ROW]
[ROW][C]13[/C][C]0.054065[/C][C]0.4153[/C][C]0.33972[/C][/ROW]
[ROW][C]14[/C][C]-0.032223[/C][C]-0.2475[/C][C]0.402685[/C][/ROW]
[ROW][C]15[/C][C]0.050872[/C][C]0.3908[/C][C]0.348692[/C][/ROW]
[ROW][C]16[/C][C]-0.032827[/C][C]-0.2521[/C][C]0.400901[/C][/ROW]
[ROW][C]17[/C][C]-0.060645[/C][C]-0.4658[/C][C]0.321529[/C][/ROW]
[ROW][C]18[/C][C]-0.036186[/C][C]-0.2779[/C][C]0.391011[/C][/ROW]
[ROW][C]19[/C][C]0.055204[/C][C]0.424[/C][C]0.336543[/C][/ROW]
[ROW][C]20[/C][C]-0.16807[/C][C]-1.291[/C][C]0.100874[/C][/ROW]
[ROW][C]21[/C][C]0.000519[/C][C]0.004[/C][C]0.498416[/C][/ROW]
[ROW][C]22[/C][C]0.01426[/C][C]0.1095[/C][C]0.456577[/C][/ROW]
[ROW][C]23[/C][C]-0.096403[/C][C]-0.7405[/C][C]0.230971[/C][/ROW]
[ROW][C]24[/C][C]0.074606[/C][C]0.5731[/C][C]0.28439[/C][/ROW]
[ROW][C]25[/C][C]0.104233[/C][C]0.8006[/C][C]0.213279[/C][/ROW]
[ROW][C]26[/C][C]0.029582[/C][C]0.2272[/C][C]0.410517[/C][/ROW]
[ROW][C]27[/C][C]-0.120027[/C][C]-0.9219[/C][C]0.180156[/C][/ROW]
[ROW][C]28[/C][C]0.077781[/C][C]0.5974[/C][C]0.276248[/C][/ROW]
[ROW][C]29[/C][C]0.008074[/C][C]0.062[/C][C]0.475379[/C][/ROW]
[ROW][C]30[/C][C]-0.040987[/C][C]-0.3148[/C][C]0.377002[/C][/ROW]
[ROW][C]31[/C][C]-0.015666[/C][C]-0.1203[/C][C]0.452313[/C][/ROW]
[ROW][C]32[/C][C]-0.023313[/C][C]-0.1791[/C][C]0.429246[/C][/ROW]
[ROW][C]33[/C][C]0.104199[/C][C]0.8004[/C][C]0.213354[/C][/ROW]
[ROW][C]34[/C][C]0.005859[/C][C]0.045[/C][C]0.482129[/C][/ROW]
[ROW][C]35[/C][C]0.053508[/C][C]0.411[/C][C]0.341281[/C][/ROW]
[ROW][C]36[/C][C]-0.009338[/C][C]-0.0717[/C][C]0.471532[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66060&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66060&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
10.467083.58770.000339
2-0.26999-2.07380.021234
30.0070220.05390.478583
40.0127610.0980.461124
5-0.18619-1.43020.078974
60.1347891.03530.152369
7-0.070321-0.54010.295566
8-0.067825-0.5210.302169
90.0273260.20990.417236
100.0534410.41050.341467
11-0.051181-0.39310.347819
12-0.302283-2.32190.011856
130.0540650.41530.33972
14-0.032223-0.24750.402685
150.0508720.39080.348692
16-0.032827-0.25210.400901
17-0.060645-0.46580.321529
18-0.036186-0.27790.391011
190.0552040.4240.336543
20-0.16807-1.2910.100874
210.0005190.0040.498416
220.014260.10950.456577
23-0.096403-0.74050.230971
240.0746060.57310.28439
250.1042330.80060.213279
260.0295820.22720.410517
27-0.120027-0.92190.180156
280.0777810.59740.276248
290.0080740.0620.475379
30-0.040987-0.31480.377002
31-0.015666-0.12030.452313
32-0.023313-0.17910.429246
330.1041990.80040.213354
340.0058590.0450.482129
350.0535080.4110.341281
36-0.009338-0.07170.471532


Figures (Output of Computation)

Input Parameters & R Code

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 = 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')