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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Tue, 07 Dec 2010 19:09:49 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/07/t1291748900442w6zs9snup97o.htm/, Retrieved Sat, 04 May 2024 01:40:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106643, Retrieved Sat, 04 May 2024 01:40:14 +0000

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User-defined keywords

Estimated Impact

124

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [(Partial) Autocorrelation Function] [Workshop 9: ACF] [2010-12-04 15:14:11] [87d60b8864dc39f7ed759c345edfb471]
-    D  [(Partial) Autocorrelation Function] [] [2010-12-07 08:48:25] [1251ac2db27b84d4a3ba43449388906b]
F    D      [(Partial) Autocorrelation Function] [computation 1] [2010-12-07 19:09:49] [4f70e6cd0867f10d298e58e8e27859b5] [Current]
-   P         [(Partial) Autocorrelation Function] [] [2010-12-14 12:02:33] [d672a41e0af7ff107c03f1d65e47fd32] 

Feedback Forum

2010-12-14 12:08:07 [Kristof Schellekens] [reply] 
Ik raad je aan om niet default als parameter te gebruiken, maar eerder 48 of 60 bij de lags. Zo is het niet alleen voor jouw makkelijker om conclusies te trekken, het zal het ook voor andere studenten het makkelijker maken om jouw conclusies te begrijpen. 
 
Hieronder een voorbeeld van jouw berekening die ik gereproduceerd heb met aangepaste lags (60): 
http://www.freestatistics.org/blog/index.php?v=date/2010/Dec/14/t12923281748ahdtlt7nqrguh1.htm/

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106643&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106643&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106643&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.069616	0.5907	0.278281
2	-0.237467	-2.015	0.023821
3	0.065734	0.5578	0.289365
4	-0.143035	-1.2137	0.114415
5	-0.210745	-1.7882	0.038973
6	0.070471	0.598	0.275869
7	-0.100935	-0.8565	0.197293
8	-0.053624	-0.455	0.325234
9	0.118363	1.0043	0.159288
10	-0.113681	-0.9646	0.168983
11	0.116397	0.9877	0.163313
12	0.466638	3.9596	8.7e-05
13	-0.040597	-0.3445	0.365746
14	-0.27176	-2.306	0.011998
15	0.056152	0.4765	0.317594
16	-0.131249	-1.1137	0.134559
17	-0.17815	-1.5117	0.0675
18	0.047122	0.3998	0.345227

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.069616 & 0.5907 & 0.278281 \tabularnewline
2 & -0.237467 & -2.015 & 0.023821 \tabularnewline
3 & 0.065734 & 0.5578 & 0.289365 \tabularnewline
4 & -0.143035 & -1.2137 & 0.114415 \tabularnewline
5 & -0.210745 & -1.7882 & 0.038973 \tabularnewline
6 & 0.070471 & 0.598 & 0.275869 \tabularnewline
7 & -0.100935 & -0.8565 & 0.197293 \tabularnewline
8 & -0.053624 & -0.455 & 0.325234 \tabularnewline
9 & 0.118363 & 1.0043 & 0.159288 \tabularnewline
10 & -0.113681 & -0.9646 & 0.168983 \tabularnewline
11 & 0.116397 & 0.9877 & 0.163313 \tabularnewline
12 & 0.466638 & 3.9596 & 8.7e-05 \tabularnewline
13 & -0.040597 & -0.3445 & 0.365746 \tabularnewline
14 & -0.27176 & -2.306 & 0.011998 \tabularnewline
15 & 0.056152 & 0.4765 & 0.317594 \tabularnewline
16 & -0.131249 & -1.1137 & 0.134559 \tabularnewline
17 & -0.17815 & -1.5117 & 0.0675 \tabularnewline
18 & 0.047122 & 0.3998 & 0.345227 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106643&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]0.069616[/C][C]0.5907[/C][C]0.278281[/C][/ROW]
[ROW][C]2[/C][C]-0.237467[/C][C]-2.015[/C][C]0.023821[/C][/ROW]
[ROW][C]3[/C][C]0.065734[/C][C]0.5578[/C][C]0.289365[/C][/ROW]
[ROW][C]4[/C][C]-0.143035[/C][C]-1.2137[/C][C]0.114415[/C][/ROW]
[ROW][C]5[/C][C]-0.210745[/C][C]-1.7882[/C][C]0.038973[/C][/ROW]
[ROW][C]6[/C][C]0.070471[/C][C]0.598[/C][C]0.275869[/C][/ROW]
[ROW][C]7[/C][C]-0.100935[/C][C]-0.8565[/C][C]0.197293[/C][/ROW]
[ROW][C]8[/C][C]-0.053624[/C][C]-0.455[/C][C]0.325234[/C][/ROW]
[ROW][C]9[/C][C]0.118363[/C][C]1.0043[/C][C]0.159288[/C][/ROW]
[ROW][C]10[/C][C]-0.113681[/C][C]-0.9646[/C][C]0.168983[/C][/ROW]
[ROW][C]11[/C][C]0.116397[/C][C]0.9877[/C][C]0.163313[/C][/ROW]
[ROW][C]12[/C][C]0.466638[/C][C]3.9596[/C][C]8.7e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.040597[/C][C]-0.3445[/C][C]0.365746[/C][/ROW]
[ROW][C]14[/C][C]-0.27176[/C][C]-2.306[/C][C]0.011998[/C][/ROW]
[ROW][C]15[/C][C]0.056152[/C][C]0.4765[/C][C]0.317594[/C][/ROW]
[ROW][C]16[/C][C]-0.131249[/C][C]-1.1137[/C][C]0.134559[/C][/ROW]
[ROW][C]17[/C][C]-0.17815[/C][C]-1.5117[/C][C]0.0675[/C][/ROW]
[ROW][C]18[/C][C]0.047122[/C][C]0.3998[/C][C]0.345227[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106643&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106643&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 k	ACF(k)	T-STAT	P-value
1	0.069616	0.5907	0.278281
2	-0.237467	-2.015	0.023821
3	0.065734	0.5578	0.289365
4	-0.143035	-1.2137	0.114415
5	-0.210745	-1.7882	0.038973
6	0.070471	0.598	0.275869
7	-0.100935	-0.8565	0.197293
8	-0.053624	-0.455	0.325234
9	0.118363	1.0043	0.159288
10	-0.113681	-0.9646	0.168983
11	0.116397	0.9877	0.163313
12	0.466638	3.9596	8.7e-05
13	-0.040597	-0.3445	0.365746
14	-0.27176	-2.306	0.011998
15	0.056152	0.4765	0.317594
16	-0.131249	-1.1137	0.134559
17	-0.17815	-1.5117	0.0675
18	0.047122	0.3998	0.345227

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.069616	0.5907	0.278281
2	-0.243493	-2.0661	0.021208
3	0.110283	0.9358	0.176256
4	-0.236013	-2.0026	0.024491
5	-0.138865	-1.1783	0.121277
6	0.003509	0.0298	0.488165
7	-0.205533	-1.744	0.042713
8	-0.005323	-0.0452	0.482049
9	-0.038661	-0.3281	0.371912
10	-0.180454	-1.5312	0.065051
11	0.181644	1.5413	0.063814
12	0.350557	2.9746	0.001995
13	-0.014839	-0.1259	0.450077
14	-0.121724	-1.0329	0.152562
15	0.044451	0.3772	0.353576
16	-0.055449	-0.4705	0.31971
17	-0.033212	-0.2818	0.389447
18	-0.08339	-0.7076	0.240743

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.069616 & 0.5907 & 0.278281 \tabularnewline
2 & -0.243493 & -2.0661 & 0.021208 \tabularnewline
3 & 0.110283 & 0.9358 & 0.176256 \tabularnewline
4 & -0.236013 & -2.0026 & 0.024491 \tabularnewline
5 & -0.138865 & -1.1783 & 0.121277 \tabularnewline
6 & 0.003509 & 0.0298 & 0.488165 \tabularnewline
7 & -0.205533 & -1.744 & 0.042713 \tabularnewline
8 & -0.005323 & -0.0452 & 0.482049 \tabularnewline
9 & -0.038661 & -0.3281 & 0.371912 \tabularnewline
10 & -0.180454 & -1.5312 & 0.065051 \tabularnewline
11 & 0.181644 & 1.5413 & 0.063814 \tabularnewline
12 & 0.350557 & 2.9746 & 0.001995 \tabularnewline
13 & -0.014839 & -0.1259 & 0.450077 \tabularnewline
14 & -0.121724 & -1.0329 & 0.152562 \tabularnewline
15 & 0.044451 & 0.3772 & 0.353576 \tabularnewline
16 & -0.055449 & -0.4705 & 0.31971 \tabularnewline
17 & -0.033212 & -0.2818 & 0.389447 \tabularnewline
18 & -0.08339 & -0.7076 & 0.240743 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106643&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]0.069616[/C][C]0.5907[/C][C]0.278281[/C][/ROW]
[ROW][C]2[/C][C]-0.243493[/C][C]-2.0661[/C][C]0.021208[/C][/ROW]
[ROW][C]3[/C][C]0.110283[/C][C]0.9358[/C][C]0.176256[/C][/ROW]
[ROW][C]4[/C][C]-0.236013[/C][C]-2.0026[/C][C]0.024491[/C][/ROW]
[ROW][C]5[/C][C]-0.138865[/C][C]-1.1783[/C][C]0.121277[/C][/ROW]
[ROW][C]6[/C][C]0.003509[/C][C]0.0298[/C][C]0.488165[/C][/ROW]
[ROW][C]7[/C][C]-0.205533[/C][C]-1.744[/C][C]0.042713[/C][/ROW]
[ROW][C]8[/C][C]-0.005323[/C][C]-0.0452[/C][C]0.482049[/C][/ROW]
[ROW][C]9[/C][C]-0.038661[/C][C]-0.3281[/C][C]0.371912[/C][/ROW]
[ROW][C]10[/C][C]-0.180454[/C][C]-1.5312[/C][C]0.065051[/C][/ROW]
[ROW][C]11[/C][C]0.181644[/C][C]1.5413[/C][C]0.063814[/C][/ROW]
[ROW][C]12[/C][C]0.350557[/C][C]2.9746[/C][C]0.001995[/C][/ROW]
[ROW][C]13[/C][C]-0.014839[/C][C]-0.1259[/C][C]0.450077[/C][/ROW]
[ROW][C]14[/C][C]-0.121724[/C][C]-1.0329[/C][C]0.152562[/C][/ROW]
[ROW][C]15[/C][C]0.044451[/C][C]0.3772[/C][C]0.353576[/C][/ROW]
[ROW][C]16[/C][C]-0.055449[/C][C]-0.4705[/C][C]0.31971[/C][/ROW]
[ROW][C]17[/C][C]-0.033212[/C][C]-0.2818[/C][C]0.389447[/C][/ROW]
[ROW][C]18[/C][C]-0.08339[/C][C]-0.7076[/C][C]0.240743[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106643&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106643&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 k	PACF(k)	T-STAT	P-value
1	0.069616	0.5907	0.278281
2	-0.243493	-2.0661	0.021208
3	0.110283	0.9358	0.176256
4	-0.236013	-2.0026	0.024491
5	-0.138865	-1.1783	0.121277
6	0.003509	0.0298	0.488165
7	-0.205533	-1.744	0.042713
8	-0.005323	-0.0452	0.482049
9	-0.038661	-0.3281	0.371912
10	-0.180454	-1.5312	0.065051
11	0.181644	1.5413	0.063814
12	0.350557	2.9746	0.001995
13	-0.014839	-0.1259	0.450077
14	-0.121724	-1.0329	0.152562
15	0.044451	0.3772	0.353576
16	-0.055449	-0.4705	0.31971
17	-0.033212	-0.2818	0.389447
18	-0.08339	-0.7076	0.240743

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code