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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Tue, 20 Dec 2016 14:54:39 +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/20/t1482242275qf8g8eq18q31o1e.htm/, Retrieved Sun, 28 Apr 2024 17:18:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301676, Retrieved Sun, 28 Apr 2024 17:18:48 +0000

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-       [(Partial) Autocorrelation Function] [seizonaliteit N15...] [2016-12-20 13:54:39] [c383a3f496d779b12e2493a523dfe438] [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	2 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 time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301676&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]

2 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301676&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301676&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	2 seconds
R Server	Big Analytics Cloud Computing Center

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.186539	-1.2513	0.108638
2	-0.099572	-0.6679	0.253789
3	0.06621	0.4442	0.329531
4	-0.147708	-0.9909	0.163528
5	0.110681	0.7425	0.230831
6	-0.354544	-2.3784	0.010848
7	0.146225	0.9809	0.165942
8	0.007233	0.0485	0.480759
9	-0.011427	-0.0767	0.469619
10	0.164006	1.1002	0.138551
11	-0.199339	-1.3372	0.093938
12	0.074022	0.4966	0.310959
13	-0.1091	-0.7319	0.234023
14	0.009119	0.0612	0.475747
15	0.056175	0.3768	0.354035
16	-0.099018	-0.6642	0.254966
17	0.059302	0.3978	0.346327

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.186539 & -1.2513 & 0.108638 \tabularnewline
2 & -0.099572 & -0.6679 & 0.253789 \tabularnewline
3 & 0.06621 & 0.4442 & 0.329531 \tabularnewline
4 & -0.147708 & -0.9909 & 0.163528 \tabularnewline
5 & 0.110681 & 0.7425 & 0.230831 \tabularnewline
6 & -0.354544 & -2.3784 & 0.010848 \tabularnewline
7 & 0.146225 & 0.9809 & 0.165942 \tabularnewline
8 & 0.007233 & 0.0485 & 0.480759 \tabularnewline
9 & -0.011427 & -0.0767 & 0.469619 \tabularnewline
10 & 0.164006 & 1.1002 & 0.138551 \tabularnewline
11 & -0.199339 & -1.3372 & 0.093938 \tabularnewline
12 & 0.074022 & 0.4966 & 0.310959 \tabularnewline
13 & -0.1091 & -0.7319 & 0.234023 \tabularnewline
14 & 0.009119 & 0.0612 & 0.475747 \tabularnewline
15 & 0.056175 & 0.3768 & 0.354035 \tabularnewline
16 & -0.099018 & -0.6642 & 0.254966 \tabularnewline
17 & 0.059302 & 0.3978 & 0.346327 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301676&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]-0.186539[/C][C]-1.2513[/C][C]0.108638[/C][/ROW]
[ROW][C]2[/C][C]-0.099572[/C][C]-0.6679[/C][C]0.253789[/C][/ROW]
[ROW][C]3[/C][C]0.06621[/C][C]0.4442[/C][C]0.329531[/C][/ROW]
[ROW][C]4[/C][C]-0.147708[/C][C]-0.9909[/C][C]0.163528[/C][/ROW]
[ROW][C]5[/C][C]0.110681[/C][C]0.7425[/C][C]0.230831[/C][/ROW]
[ROW][C]6[/C][C]-0.354544[/C][C]-2.3784[/C][C]0.010848[/C][/ROW]
[ROW][C]7[/C][C]0.146225[/C][C]0.9809[/C][C]0.165942[/C][/ROW]
[ROW][C]8[/C][C]0.007233[/C][C]0.0485[/C][C]0.480759[/C][/ROW]
[ROW][C]9[/C][C]-0.011427[/C][C]-0.0767[/C][C]0.469619[/C][/ROW]
[ROW][C]10[/C][C]0.164006[/C][C]1.1002[/C][C]0.138551[/C][/ROW]
[ROW][C]11[/C][C]-0.199339[/C][C]-1.3372[/C][C]0.093938[/C][/ROW]
[ROW][C]12[/C][C]0.074022[/C][C]0.4966[/C][C]0.310959[/C][/ROW]
[ROW][C]13[/C][C]-0.1091[/C][C]-0.7319[/C][C]0.234023[/C][/ROW]
[ROW][C]14[/C][C]0.009119[/C][C]0.0612[/C][C]0.475747[/C][/ROW]
[ROW][C]15[/C][C]0.056175[/C][C]0.3768[/C][C]0.354035[/C][/ROW]
[ROW][C]16[/C][C]-0.099018[/C][C]-0.6642[/C][C]0.254966[/C][/ROW]
[ROW][C]17[/C][C]0.059302[/C][C]0.3978[/C][C]0.346327[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301676&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301676&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	-0.186539	-1.2513	0.108638
2	-0.099572	-0.6679	0.253789
3	0.06621	0.4442	0.329531
4	-0.147708	-0.9909	0.163528
5	0.110681	0.7425	0.230831
6	-0.354544	-2.3784	0.010848
7	0.146225	0.9809	0.165942
8	0.007233	0.0485	0.480759
9	-0.011427	-0.0767	0.469619
10	0.164006	1.1002	0.138551
11	-0.199339	-1.3372	0.093938
12	0.074022	0.4966	0.310959
13	-0.1091	-0.7319	0.234023
14	0.009119	0.0612	0.475747
15	0.056175	0.3768	0.354035
16	-0.099018	-0.6642	0.254966
17	0.059302	0.3978	0.346327

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.186539	-1.2513	0.108638
2	-0.139213	-0.9339	0.177678
3	0.02016	0.1352	0.446513
4	-0.151671	-1.0174	0.157192
5	0.065987	0.4427	0.330069
6	-0.387866	-2.6019	0.006253
7	0.061483	0.4124	0.340987
8	-0.130255	-0.8738	0.193439
9	0.082115	0.5508	0.292234
10	0.020483	0.1374	0.445663
11	-0.090288	-0.6057	0.273888
12	-0.117911	-0.791	0.216555
13	-0.113225	-0.7595	0.225747
14	-0.029468	-0.1977	0.422094
15	-0.009951	-0.0668	0.473538
16	-0.020746	-0.1392	0.444969
17	-0.13661	-0.9164	0.18217

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.186539 & -1.2513 & 0.108638 \tabularnewline
2 & -0.139213 & -0.9339 & 0.177678 \tabularnewline
3 & 0.02016 & 0.1352 & 0.446513 \tabularnewline
4 & -0.151671 & -1.0174 & 0.157192 \tabularnewline
5 & 0.065987 & 0.4427 & 0.330069 \tabularnewline
6 & -0.387866 & -2.6019 & 0.006253 \tabularnewline
7 & 0.061483 & 0.4124 & 0.340987 \tabularnewline
8 & -0.130255 & -0.8738 & 0.193439 \tabularnewline
9 & 0.082115 & 0.5508 & 0.292234 \tabularnewline
10 & 0.020483 & 0.1374 & 0.445663 \tabularnewline
11 & -0.090288 & -0.6057 & 0.273888 \tabularnewline
12 & -0.117911 & -0.791 & 0.216555 \tabularnewline
13 & -0.113225 & -0.7595 & 0.225747 \tabularnewline
14 & -0.029468 & -0.1977 & 0.422094 \tabularnewline
15 & -0.009951 & -0.0668 & 0.473538 \tabularnewline
16 & -0.020746 & -0.1392 & 0.444969 \tabularnewline
17 & -0.13661 & -0.9164 & 0.18217 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301676&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]-0.186539[/C][C]-1.2513[/C][C]0.108638[/C][/ROW]
[ROW][C]2[/C][C]-0.139213[/C][C]-0.9339[/C][C]0.177678[/C][/ROW]
[ROW][C]3[/C][C]0.02016[/C][C]0.1352[/C][C]0.446513[/C][/ROW]
[ROW][C]4[/C][C]-0.151671[/C][C]-1.0174[/C][C]0.157192[/C][/ROW]
[ROW][C]5[/C][C]0.065987[/C][C]0.4427[/C][C]0.330069[/C][/ROW]
[ROW][C]6[/C][C]-0.387866[/C][C]-2.6019[/C][C]0.006253[/C][/ROW]
[ROW][C]7[/C][C]0.061483[/C][C]0.4124[/C][C]0.340987[/C][/ROW]
[ROW][C]8[/C][C]-0.130255[/C][C]-0.8738[/C][C]0.193439[/C][/ROW]
[ROW][C]9[/C][C]0.082115[/C][C]0.5508[/C][C]0.292234[/C][/ROW]
[ROW][C]10[/C][C]0.020483[/C][C]0.1374[/C][C]0.445663[/C][/ROW]
[ROW][C]11[/C][C]-0.090288[/C][C]-0.6057[/C][C]0.273888[/C][/ROW]
[ROW][C]12[/C][C]-0.117911[/C][C]-0.791[/C][C]0.216555[/C][/ROW]
[ROW][C]13[/C][C]-0.113225[/C][C]-0.7595[/C][C]0.225747[/C][/ROW]
[ROW][C]14[/C][C]-0.029468[/C][C]-0.1977[/C][C]0.422094[/C][/ROW]
[ROW][C]15[/C][C]-0.009951[/C][C]-0.0668[/C][C]0.473538[/C][/ROW]
[ROW][C]16[/C][C]-0.020746[/C][C]-0.1392[/C][C]0.444969[/C][/ROW]
[ROW][C]17[/C][C]-0.13661[/C][C]-0.9164[/C][C]0.18217[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301676&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301676&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	-0.186539	-1.2513	0.108638
2	-0.139213	-0.9339	0.177678
3	0.02016	0.1352	0.446513
4	-0.151671	-1.0174	0.157192
5	0.065987	0.4427	0.330069
6	-0.387866	-2.6019	0.006253
7	0.061483	0.4124	0.340987
8	-0.130255	-0.8738	0.193439
9	0.082115	0.5508	0.292234
10	0.020483	0.1374	0.445663
11	-0.090288	-0.6057	0.273888
12	-0.117911	-0.791	0.216555
13	-0.113225	-0.7595	0.225747
14	-0.029468	-0.1977	0.422094
15	-0.009951	-0.0668	0.473538
16	-0.020746	-0.1392	0.444969
17	-0.13661	-0.9164	0.18217

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 = 6 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 6 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;

R code (references can be found in the software module):

par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '6'
par4 <- '1'
par3 <- '0'
par2 <- '1'
par1 <- 'Default'
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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Input Parameters & R Code