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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 23 Dec 2016 22:50:30 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/23/t1482529864gkf21zbmelo4l0c.htm/, Retrieved Tue, 07 May 2024 14:29:53 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=303055, Retrieved Tue, 07 May 2024 14:29:53 +0000

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

-       [(Partial) Autocorrelation Function] [sjkjks] [2016-12-23 21:50:30] [2a3a89286ec83ecc146a1d371615e68b] [Current]

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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	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=303055&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=303055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=303055&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	Big Analytics Cloud Computing Center

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.133936	-0.8147	0.210228
2	-0.119127	-0.7246	0.236621
3	-0.163072	-0.9919	0.163838
4	0.01726	0.105	0.458476
5	0.265546	1.6153	0.057376
6	-0.050529	-0.3074	0.380148
7	0.03519	0.2141	0.41584
8	0.06471	0.3936	0.348063
9	-0.056435	-0.3433	0.366666
10	-0.042709	-0.2598	0.398234
11	-0.03336	-0.2029	0.420155
12	-0.056934	-0.3463	0.365533
13	0.08383	0.5099	0.306569
14	-0.034609	-0.2105	0.417208
15	-0.042495	-0.2585	0.398732

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.133936 & -0.8147 & 0.210228 \tabularnewline
2 & -0.119127 & -0.7246 & 0.236621 \tabularnewline
3 & -0.163072 & -0.9919 & 0.163838 \tabularnewline
4 & 0.01726 & 0.105 & 0.458476 \tabularnewline
5 & 0.265546 & 1.6153 & 0.057376 \tabularnewline
6 & -0.050529 & -0.3074 & 0.380148 \tabularnewline
7 & 0.03519 & 0.2141 & 0.41584 \tabularnewline
8 & 0.06471 & 0.3936 & 0.348063 \tabularnewline
9 & -0.056435 & -0.3433 & 0.366666 \tabularnewline
10 & -0.042709 & -0.2598 & 0.398234 \tabularnewline
11 & -0.03336 & -0.2029 & 0.420155 \tabularnewline
12 & -0.056934 & -0.3463 & 0.365533 \tabularnewline
13 & 0.08383 & 0.5099 & 0.306569 \tabularnewline
14 & -0.034609 & -0.2105 & 0.417208 \tabularnewline
15 & -0.042495 & -0.2585 & 0.398732 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=303055&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]-0.133936[/C][C]-0.8147[/C][C]0.210228[/C][/ROW]
[ROW][C]2[/C][C]-0.119127[/C][C]-0.7246[/C][C]0.236621[/C][/ROW]
[ROW][C]3[/C][C]-0.163072[/C][C]-0.9919[/C][C]0.163838[/C][/ROW]
[ROW][C]4[/C][C]0.01726[/C][C]0.105[/C][C]0.458476[/C][/ROW]
[ROW][C]5[/C][C]0.265546[/C][C]1.6153[/C][C]0.057376[/C][/ROW]
[ROW][C]6[/C][C]-0.050529[/C][C]-0.3074[/C][C]0.380148[/C][/ROW]
[ROW][C]7[/C][C]0.03519[/C][C]0.2141[/C][C]0.41584[/C][/ROW]
[ROW][C]8[/C][C]0.06471[/C][C]0.3936[/C][C]0.348063[/C][/ROW]
[ROW][C]9[/C][C]-0.056435[/C][C]-0.3433[/C][C]0.366666[/C][/ROW]
[ROW][C]10[/C][C]-0.042709[/C][C]-0.2598[/C][C]0.398234[/C][/ROW]
[ROW][C]11[/C][C]-0.03336[/C][C]-0.2029[/C][C]0.420155[/C][/ROW]
[ROW][C]12[/C][C]-0.056934[/C][C]-0.3463[/C][C]0.365533[/C][/ROW]
[ROW][C]13[/C][C]0.08383[/C][C]0.5099[/C][C]0.306569[/C][/ROW]
[ROW][C]14[/C][C]-0.034609[/C][C]-0.2105[/C][C]0.417208[/C][/ROW]
[ROW][C]15[/C][C]-0.042495[/C][C]-0.2585[/C][C]0.398732[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=303055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=303055&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	-0.133936	-0.8147	0.210228
2	-0.119127	-0.7246	0.236621
3	-0.163072	-0.9919	0.163838
4	0.01726	0.105	0.458476
5	0.265546	1.6153	0.057376
6	-0.050529	-0.3074	0.380148
7	0.03519	0.2141	0.41584
8	0.06471	0.3936	0.348063
9	-0.056435	-0.3433	0.366666
10	-0.042709	-0.2598	0.398234
11	-0.03336	-0.2029	0.420155
12	-0.056934	-0.3463	0.365533
13	0.08383	0.5099	0.306569
14	-0.034609	-0.2105	0.417208
15	-0.042495	-0.2585	0.398732

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.133936	-0.8147	0.210228
2	-0.13957	-0.849	0.200679
3	-0.207645	-1.2631	0.107236
4	-0.065735	-0.3998	0.345783
5	0.222567	1.3538	0.092003
6	-0.002619	-0.0159	0.493687
7	0.099901	0.6077	0.273557
8	0.18985	1.1548	0.127785
9	-0.004929	-0.03	0.488122
10	-0.077634	-0.4722	0.319768
11	-0.023272	-0.1416	0.444098
12	-0.169261	-1.0296	0.154946
13	-0.056843	-0.3458	0.365741
14	-0.046664	-0.2838	0.389056
15	-0.078128	-0.4752	0.318708

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.133936 & -0.8147 & 0.210228 \tabularnewline
2 & -0.13957 & -0.849 & 0.200679 \tabularnewline
3 & -0.207645 & -1.2631 & 0.107236 \tabularnewline
4 & -0.065735 & -0.3998 & 0.345783 \tabularnewline
5 & 0.222567 & 1.3538 & 0.092003 \tabularnewline
6 & -0.002619 & -0.0159 & 0.493687 \tabularnewline
7 & 0.099901 & 0.6077 & 0.273557 \tabularnewline
8 & 0.18985 & 1.1548 & 0.127785 \tabularnewline
9 & -0.004929 & -0.03 & 0.488122 \tabularnewline
10 & -0.077634 & -0.4722 & 0.319768 \tabularnewline
11 & -0.023272 & -0.1416 & 0.444098 \tabularnewline
12 & -0.169261 & -1.0296 & 0.154946 \tabularnewline
13 & -0.056843 & -0.3458 & 0.365741 \tabularnewline
14 & -0.046664 & -0.2838 & 0.389056 \tabularnewline
15 & -0.078128 & -0.4752 & 0.318708 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=303055&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]-0.133936[/C][C]-0.8147[/C][C]0.210228[/C][/ROW]
[ROW][C]2[/C][C]-0.13957[/C][C]-0.849[/C][C]0.200679[/C][/ROW]
[ROW][C]3[/C][C]-0.207645[/C][C]-1.2631[/C][C]0.107236[/C][/ROW]
[ROW][C]4[/C][C]-0.065735[/C][C]-0.3998[/C][C]0.345783[/C][/ROW]
[ROW][C]5[/C][C]0.222567[/C][C]1.3538[/C][C]0.092003[/C][/ROW]
[ROW][C]6[/C][C]-0.002619[/C][C]-0.0159[/C][C]0.493687[/C][/ROW]
[ROW][C]7[/C][C]0.099901[/C][C]0.6077[/C][C]0.273557[/C][/ROW]
[ROW][C]8[/C][C]0.18985[/C][C]1.1548[/C][C]0.127785[/C][/ROW]
[ROW][C]9[/C][C]-0.004929[/C][C]-0.03[/C][C]0.488122[/C][/ROW]
[ROW][C]10[/C][C]-0.077634[/C][C]-0.4722[/C][C]0.319768[/C][/ROW]
[ROW][C]11[/C][C]-0.023272[/C][C]-0.1416[/C][C]0.444098[/C][/ROW]
[ROW][C]12[/C][C]-0.169261[/C][C]-1.0296[/C][C]0.154946[/C][/ROW]
[ROW][C]13[/C][C]-0.056843[/C][C]-0.3458[/C][C]0.365741[/C][/ROW]
[ROW][C]14[/C][C]-0.046664[/C][C]-0.2838[/C][C]0.389056[/C][/ROW]
[ROW][C]15[/C][C]-0.078128[/C][C]-0.4752[/C][C]0.318708[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=303055&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=303055&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	-0.133936	-0.8147	0.210228
2	-0.13957	-0.849	0.200679
3	-0.207645	-1.2631	0.107236
4	-0.065735	-0.3998	0.345783
5	0.222567	1.3538	0.092003
6	-0.002619	-0.0159	0.493687
7	0.099901	0.6077	0.273557
8	0.18985	1.1548	0.127785
9	-0.004929	-0.03	0.488122
10	-0.077634	-0.4722	0.319768
11	-0.023272	-0.1416	0.444098
12	-0.169261	-1.0296	0.154946
13	-0.056843	-0.3458	0.365741
14	-0.046664	-0.2838	0.389056
15	-0.078128	-0.4752	0.318708

Figure 1

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Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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')

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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code