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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, 06 Dec 2011 03:18:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/06/t1323159569l59mg7kdmszjg54.htm/, Retrieved Sun, 28 Apr 2024 19:14:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151374, Retrieved Sun, 28 Apr 2024 19:14:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMPD  [(Partial) Autocorrelation Function] [ACF (d=0, D=0)] [2011-12-06 08:00:15] [bcad5ea7a7be31884500e96b7abaff18]
- R P     [(Partial) Autocorrelation Function] [ACF (d=1 en D=0)] [2011-12-06 08:08:10] [bcad5ea7a7be31884500e96b7abaff18]
-   P       [(Partial) Autocorrelation Function] [ACF (d=0, D=1)] [2011-12-06 08:17:43] [bcad5ea7a7be31884500e96b7abaff18]
-   P           [(Partial) Autocorrelation Function] [ACF (d=1, D=1)] [2011-12-06 08:18:59] [d14d64ba86ecc27fb5997ae1bd82937b] [Current]
- RMP             [Spectral Analysis] [CP (d=0, D=0)] [2011-12-06 08:24:51] [bcad5ea7a7be31884500e96b7abaff18]
- R P               [Spectral Analysis] [CP (d=1, D=0)] [2011-12-06 08:27:06] [bcad5ea7a7be31884500e96b7abaff18]
-   P                 [Spectral Analysis] [CP (d=0, D=1)] [2011-12-06 08:28:42] [bcad5ea7a7be31884500e96b7abaff18]
-   P                   [Spectral Analysis] [CP (d=1, D=1)] [2011-12-06 08:30:04] [bcad5ea7a7be31884500e96b7abaff18]
- RMP                   [Variance Reduction Matrix] [VRM ] [2011-12-06 08:41:26] [bcad5ea7a7be31884500e96b7abaff18]
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Dataseries X:
2851
2672
2755
2721
2946
3036
2282
2212
2922
4301
5764
7132
2541
2475
3031
3266
3776
3230
3028
1759
3595
4474
6838
8357
3113
3006
4047
3523
3937
3986
3260
1573
3528
5211
7614
9254
5375
3088
3718
4514
4520
4539
3663
1643
4739
5428
8314
10651
3633
4292
4154
4121
4647
4753
3965
1723
5048
6922
9858
11331
4016
3957
4510
4276
4968
4677
3523
1821
5222
6873
10803
13916
2639
2899
3370
3740
2927
3986
4217
1738
5221
6424
9842
13076
3934
3162
4286
4676
5010
4874
4633
1659
5951
6981
9851
12670




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151374&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151374&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151374&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.415099-3.78170.000146
2-0.097133-0.88490.189377
30.083680.76240.224004
4-0.006911-0.0630.474975
5-0.087402-0.79630.214074
6-0.023921-0.21790.414008
70.0616850.5620.287822
80.0654710.59650.276244
9-0.115703-1.05410.147447
100.0705790.6430.260997
110.1196351.08990.13945
12-0.39925-3.63730.000239
130.3537313.22260.000908
14-0.035456-0.3230.373748
15-0.083205-0.7580.225289
16-0.056746-0.5170.303272
170.036710.33440.369443
180.1120941.02120.155058
19-0.111098-1.01220.157204

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.415099 & -3.7817 & 0.000146 \tabularnewline
2 & -0.097133 & -0.8849 & 0.189377 \tabularnewline
3 & 0.08368 & 0.7624 & 0.224004 \tabularnewline
4 & -0.006911 & -0.063 & 0.474975 \tabularnewline
5 & -0.087402 & -0.7963 & 0.214074 \tabularnewline
6 & -0.023921 & -0.2179 & 0.414008 \tabularnewline
7 & 0.061685 & 0.562 & 0.287822 \tabularnewline
8 & 0.065471 & 0.5965 & 0.276244 \tabularnewline
9 & -0.115703 & -1.0541 & 0.147447 \tabularnewline
10 & 0.070579 & 0.643 & 0.260997 \tabularnewline
11 & 0.119635 & 1.0899 & 0.13945 \tabularnewline
12 & -0.39925 & -3.6373 & 0.000239 \tabularnewline
13 & 0.353731 & 3.2226 & 0.000908 \tabularnewline
14 & -0.035456 & -0.323 & 0.373748 \tabularnewline
15 & -0.083205 & -0.758 & 0.225289 \tabularnewline
16 & -0.056746 & -0.517 & 0.303272 \tabularnewline
17 & 0.03671 & 0.3344 & 0.369443 \tabularnewline
18 & 0.112094 & 1.0212 & 0.155058 \tabularnewline
19 & -0.111098 & -1.0122 & 0.157204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151374&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]-0.415099[/C][C]-3.7817[/C][C]0.000146[/C][/ROW]
[ROW][C]2[/C][C]-0.097133[/C][C]-0.8849[/C][C]0.189377[/C][/ROW]
[ROW][C]3[/C][C]0.08368[/C][C]0.7624[/C][C]0.224004[/C][/ROW]
[ROW][C]4[/C][C]-0.006911[/C][C]-0.063[/C][C]0.474975[/C][/ROW]
[ROW][C]5[/C][C]-0.087402[/C][C]-0.7963[/C][C]0.214074[/C][/ROW]
[ROW][C]6[/C][C]-0.023921[/C][C]-0.2179[/C][C]0.414008[/C][/ROW]
[ROW][C]7[/C][C]0.061685[/C][C]0.562[/C][C]0.287822[/C][/ROW]
[ROW][C]8[/C][C]0.065471[/C][C]0.5965[/C][C]0.276244[/C][/ROW]
[ROW][C]9[/C][C]-0.115703[/C][C]-1.0541[/C][C]0.147447[/C][/ROW]
[ROW][C]10[/C][C]0.070579[/C][C]0.643[/C][C]0.260997[/C][/ROW]
[ROW][C]11[/C][C]0.119635[/C][C]1.0899[/C][C]0.13945[/C][/ROW]
[ROW][C]12[/C][C]-0.39925[/C][C]-3.6373[/C][C]0.000239[/C][/ROW]
[ROW][C]13[/C][C]0.353731[/C][C]3.2226[/C][C]0.000908[/C][/ROW]
[ROW][C]14[/C][C]-0.035456[/C][C]-0.323[/C][C]0.373748[/C][/ROW]
[ROW][C]15[/C][C]-0.083205[/C][C]-0.758[/C][C]0.225289[/C][/ROW]
[ROW][C]16[/C][C]-0.056746[/C][C]-0.517[/C][C]0.303272[/C][/ROW]
[ROW][C]17[/C][C]0.03671[/C][C]0.3344[/C][C]0.369443[/C][/ROW]
[ROW][C]18[/C][C]0.112094[/C][C]1.0212[/C][C]0.155058[/C][/ROW]
[ROW][C]19[/C][C]-0.111098[/C][C]-1.0122[/C][C]0.157204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151374&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151374&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
1-0.415099-3.78170.000146
2-0.097133-0.88490.189377
30.083680.76240.224004
4-0.006911-0.0630.474975
5-0.087402-0.79630.214074
6-0.023921-0.21790.414008
70.0616850.5620.287822
80.0654710.59650.276244
9-0.115703-1.05410.147447
100.0705790.6430.260997
110.1196351.08990.13945
12-0.39925-3.63730.000239
130.3537313.22260.000908
14-0.035456-0.3230.373748
15-0.083205-0.7580.225289
16-0.056746-0.5170.303272
170.036710.33440.369443
180.1120941.02120.155058
19-0.111098-1.01220.157204







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.415099-3.78170.000146
2-0.325532-2.96570.001971
3-0.141751-1.29140.100072
4-0.07591-0.69160.245568
5-0.145566-1.32620.094211
6-0.193555-1.76340.040759
7-0.123421-1.12440.132037
80.0192780.17560.430507
9-0.082882-0.75510.226167
10-0.022625-0.20610.418601
110.1468921.33830.092234
12-0.354968-3.23390.000877
130.0696720.63470.263672
140.0430320.3920.348016
150.011360.10350.458911
16-0.125362-1.14210.128348
17-0.177313-1.61540.05501
180.0335250.30540.380403
19-0.019712-0.17960.428957

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.415099 & -3.7817 & 0.000146 \tabularnewline
2 & -0.325532 & -2.9657 & 0.001971 \tabularnewline
3 & -0.141751 & -1.2914 & 0.100072 \tabularnewline
4 & -0.07591 & -0.6916 & 0.245568 \tabularnewline
5 & -0.145566 & -1.3262 & 0.094211 \tabularnewline
6 & -0.193555 & -1.7634 & 0.040759 \tabularnewline
7 & -0.123421 & -1.1244 & 0.132037 \tabularnewline
8 & 0.019278 & 0.1756 & 0.430507 \tabularnewline
9 & -0.082882 & -0.7551 & 0.226167 \tabularnewline
10 & -0.022625 & -0.2061 & 0.418601 \tabularnewline
11 & 0.146892 & 1.3383 & 0.092234 \tabularnewline
12 & -0.354968 & -3.2339 & 0.000877 \tabularnewline
13 & 0.069672 & 0.6347 & 0.263672 \tabularnewline
14 & 0.043032 & 0.392 & 0.348016 \tabularnewline
15 & 0.01136 & 0.1035 & 0.458911 \tabularnewline
16 & -0.125362 & -1.1421 & 0.128348 \tabularnewline
17 & -0.177313 & -1.6154 & 0.05501 \tabularnewline
18 & 0.033525 & 0.3054 & 0.380403 \tabularnewline
19 & -0.019712 & -0.1796 & 0.428957 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151374&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]-0.415099[/C][C]-3.7817[/C][C]0.000146[/C][/ROW]
[ROW][C]2[/C][C]-0.325532[/C][C]-2.9657[/C][C]0.001971[/C][/ROW]
[ROW][C]3[/C][C]-0.141751[/C][C]-1.2914[/C][C]0.100072[/C][/ROW]
[ROW][C]4[/C][C]-0.07591[/C][C]-0.6916[/C][C]0.245568[/C][/ROW]
[ROW][C]5[/C][C]-0.145566[/C][C]-1.3262[/C][C]0.094211[/C][/ROW]
[ROW][C]6[/C][C]-0.193555[/C][C]-1.7634[/C][C]0.040759[/C][/ROW]
[ROW][C]7[/C][C]-0.123421[/C][C]-1.1244[/C][C]0.132037[/C][/ROW]
[ROW][C]8[/C][C]0.019278[/C][C]0.1756[/C][C]0.430507[/C][/ROW]
[ROW][C]9[/C][C]-0.082882[/C][C]-0.7551[/C][C]0.226167[/C][/ROW]
[ROW][C]10[/C][C]-0.022625[/C][C]-0.2061[/C][C]0.418601[/C][/ROW]
[ROW][C]11[/C][C]0.146892[/C][C]1.3383[/C][C]0.092234[/C][/ROW]
[ROW][C]12[/C][C]-0.354968[/C][C]-3.2339[/C][C]0.000877[/C][/ROW]
[ROW][C]13[/C][C]0.069672[/C][C]0.6347[/C][C]0.263672[/C][/ROW]
[ROW][C]14[/C][C]0.043032[/C][C]0.392[/C][C]0.348016[/C][/ROW]
[ROW][C]15[/C][C]0.01136[/C][C]0.1035[/C][C]0.458911[/C][/ROW]
[ROW][C]16[/C][C]-0.125362[/C][C]-1.1421[/C][C]0.128348[/C][/ROW]
[ROW][C]17[/C][C]-0.177313[/C][C]-1.6154[/C][C]0.05501[/C][/ROW]
[ROW][C]18[/C][C]0.033525[/C][C]0.3054[/C][C]0.380403[/C][/ROW]
[ROW][C]19[/C][C]-0.019712[/C][C]-0.1796[/C][C]0.428957[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151374&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151374&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
1-0.415099-3.78170.000146
2-0.325532-2.96570.001971
3-0.141751-1.29140.100072
4-0.07591-0.69160.245568
5-0.145566-1.32620.094211
6-0.193555-1.76340.040759
7-0.123421-1.12440.132037
80.0192780.17560.430507
9-0.082882-0.75510.226167
10-0.022625-0.20610.418601
110.1468921.33830.092234
12-0.354968-3.23390.000877
130.0696720.63470.263672
140.0430320.3920.348016
150.011360.10350.458911
16-0.125362-1.14210.128348
17-0.177313-1.61540.05501
180.0335250.30540.380403
19-0.019712-0.17960.428957



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')