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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Sat, 17 Dec 2016 14:40:58 +0100

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/2016/Dec/17/t14819820779aem63b062s7zdb.htm/, Retrieved Thu, 02 May 2024 05:20:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300786, Retrieved Thu, 02 May 2024 05:20:40 +0000

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Original text written by user:

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No (this computation is public)

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Estimated Impact

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

-       [(Partial) Autocorrelation Function] [N1179 ACF II] [2016-12-17 13:40:58] [2e11ca31a00cf8de75c33c1af2d59434] [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=300786&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=300786&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300786&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	0.233328	0.4667	0.332514
2	-0.499708	-0.9994	0.187076
3	-0.233621	-0.4672	0.332322
4	NA	NA	NA
5	NA	NA	NA
6	NA	NA	NA
7	NA	NA	NA
8	NA	NA	NA
9	NA	NA	NA
10	NA	NA	NA
11	NA	NA	NA
12	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.233328 & 0.4667 & 0.332514 \tabularnewline
2 & -0.499708 & -0.9994 & 0.187076 \tabularnewline
3 & -0.233621 & -0.4672 & 0.332322 \tabularnewline
4 & NA & NA & NA \tabularnewline
5 & NA & NA & NA \tabularnewline
6 & NA & NA & NA \tabularnewline
7 & NA & NA & NA \tabularnewline
8 & NA & NA & NA \tabularnewline
9 & NA & NA & NA \tabularnewline
10 & NA & NA & NA \tabularnewline
11 & NA & NA & NA \tabularnewline
12 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300786&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]0.233328[/C][C]0.4667[/C][C]0.332514[/C][/ROW]
[ROW][C]2[/C][C]-0.499708[/C][C]-0.9994[/C][C]0.187076[/C][/ROW]
[ROW][C]3[/C][C]-0.233621[/C][C]-0.4672[/C][C]0.332322[/C][/ROW]
[ROW][C]4[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]8[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]9[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]10[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]11[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]12[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300786&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300786&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	0.233328	0.4667	0.332514
2	-0.499708	-0.9994	0.187076
3	-0.233621	-0.4672	0.332322
4	NA	NA	NA
5	NA	NA	NA
6	NA	NA	NA
7	NA	NA	NA
8	NA	NA	NA
9	NA	NA	NA
10	NA	NA	NA
11	NA	NA	NA
12	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.233328	0.4667	0.332514
2	-0.586056	-1.1721	0.153099
3	0.141835	0.2837	0.39537
4	NA	NA	NA
5	NA	NA	NA
6	NA	NA	NA
7	NA	NA	NA
8	NA	NA	NA
9	NA	NA	NA
10	NA	NA	NA
11	NA	NA	NA
12	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.233328 & 0.4667 & 0.332514 \tabularnewline
2 & -0.586056 & -1.1721 & 0.153099 \tabularnewline
3 & 0.141835 & 0.2837 & 0.39537 \tabularnewline
4 & NA & NA & NA \tabularnewline
5 & NA & NA & NA \tabularnewline
6 & NA & NA & NA \tabularnewline
7 & NA & NA & NA \tabularnewline
8 & NA & NA & NA \tabularnewline
9 & NA & NA & NA \tabularnewline
10 & NA & NA & NA \tabularnewline
11 & NA & NA & NA \tabularnewline
12 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300786&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]0.233328[/C][C]0.4667[/C][C]0.332514[/C][/ROW]
[ROW][C]2[/C][C]-0.586056[/C][C]-1.1721[/C][C]0.153099[/C][/ROW]
[ROW][C]3[/C][C]0.141835[/C][C]0.2837[/C][C]0.39537[/C][/ROW]
[ROW][C]4[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]8[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]9[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]10[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]11[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]12[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300786&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300786&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	0.233328	0.4667	0.332514
2	-0.586056	-1.1721	0.153099
3	0.141835	0.2837	0.39537
4	NA	NA	NA
5	NA	NA	NA
6	NA	NA	NA
7	NA	NA	NA
8	NA	NA	NA
9	NA	NA	NA
10	NA	NA	NA
11	NA	NA	NA
12	NA	NA	NA

Figure 1

PNG link

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 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 0 ; 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)
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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Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code