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Author

*Unverified author*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Sat, 31 Mar 2012 08:54:41 -0400

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/2012/Mar/31/t1333198632s5xlp08gl8cu64t.htm/, Retrieved Tue, 30 Apr 2024 16:02:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164218, Retrieved Tue, 30 Apr 2024 16:02:02 +0000

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Estimated Impact

112

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

-       [(Partial) Autocorrelation Function] [] [2012-03-31 12:54:41] [426bb746e0076029d53908613853082a] [Current]

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2,07
2,08
2,08
2,08
2,09
2,09
2,09
2,1
2,1
2,1
2,11
2,11
2,11
2,13
2,18
2,2
2,21
2,21
2,22
2,22
2,23
2,23
2,23
2,23
2,24
2,25
2,26
2,27
2,28
2,29
2,3
2,3
2,3
2,32
2,32
2,32
2,33
2,34
2,34
2,34
2,35
2,35
2,36
2,37
2,37
2,37
2,38
2,38
2,38
2,39
2,4
2,41
2,42
2,43
2,43
2,43
2,43
2,44
2,44
2,45

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	'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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164218&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]2 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=164218&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164218&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	'Gertrude Mary Cox' @ cox.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.953267	7.384	0
2	0.907008	7.0257	0
3	0.85826	6.6481	0
4	0.808903	6.2657	0
5	0.759088	5.8799	0
6	0.707614	5.4812	0
7	0.653414	5.0613	2e-06
8	0.601228	4.6571	9e-06
9	0.549501	4.2564	3.7e-05
10	0.497521	3.8538	0.000143
11	0.446964	3.4622	0.000497
12	0.396153	3.0686	0.001613
13	0.342972	2.6567	0.005048
14	0.291245	2.256	0.013865
15	0.251197	1.9458	0.028186
16	0.21367	1.6551	0.051565
17	0.176276	1.3654	0.088608

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953267 & 7.384 & 0 \tabularnewline
2 & 0.907008 & 7.0257 & 0 \tabularnewline
3 & 0.85826 & 6.6481 & 0 \tabularnewline
4 & 0.808903 & 6.2657 & 0 \tabularnewline
5 & 0.759088 & 5.8799 & 0 \tabularnewline
6 & 0.707614 & 5.4812 & 0 \tabularnewline
7 & 0.653414 & 5.0613 & 2e-06 \tabularnewline
8 & 0.601228 & 4.6571 & 9e-06 \tabularnewline
9 & 0.549501 & 4.2564 & 3.7e-05 \tabularnewline
10 & 0.497521 & 3.8538 & 0.000143 \tabularnewline
11 & 0.446964 & 3.4622 & 0.000497 \tabularnewline
12 & 0.396153 & 3.0686 & 0.001613 \tabularnewline
13 & 0.342972 & 2.6567 & 0.005048 \tabularnewline
14 & 0.291245 & 2.256 & 0.013865 \tabularnewline
15 & 0.251197 & 1.9458 & 0.028186 \tabularnewline
16 & 0.21367 & 1.6551 & 0.051565 \tabularnewline
17 & 0.176276 & 1.3654 & 0.088608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164218&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]0.953267[/C][C]7.384[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.907008[/C][C]7.0257[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.85826[/C][C]6.6481[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.808903[/C][C]6.2657[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.759088[/C][C]5.8799[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.707614[/C][C]5.4812[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.653414[/C][C]5.0613[/C][C]2e-06[/C][/ROW]
[ROW][C]8[/C][C]0.601228[/C][C]4.6571[/C][C]9e-06[/C][/ROW]
[ROW][C]9[/C][C]0.549501[/C][C]4.2564[/C][C]3.7e-05[/C][/ROW]
[ROW][C]10[/C][C]0.497521[/C][C]3.8538[/C][C]0.000143[/C][/ROW]
[ROW][C]11[/C][C]0.446964[/C][C]3.4622[/C][C]0.000497[/C][/ROW]
[ROW][C]12[/C][C]0.396153[/C][C]3.0686[/C][C]0.001613[/C][/ROW]
[ROW][C]13[/C][C]0.342972[/C][C]2.6567[/C][C]0.005048[/C][/ROW]
[ROW][C]14[/C][C]0.291245[/C][C]2.256[/C][C]0.013865[/C][/ROW]
[ROW][C]15[/C][C]0.251197[/C][C]1.9458[/C][C]0.028186[/C][/ROW]
[ROW][C]16[/C][C]0.21367[/C][C]1.6551[/C][C]0.051565[/C][/ROW]
[ROW][C]17[/C][C]0.176276[/C][C]1.3654[/C][C]0.088608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164218&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164218&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	0.953267	7.384	0
2	0.907008	7.0257	0
3	0.85826	6.6481	0
4	0.808903	6.2657	0
5	0.759088	5.8799	0
6	0.707614	5.4812	0
7	0.653414	5.0613	2e-06
8	0.601228	4.6571	9e-06
9	0.549501	4.2564	3.7e-05
10	0.497521	3.8538	0.000143
11	0.446964	3.4622	0.000497
12	0.396153	3.0686	0.001613
13	0.342972	2.6567	0.005048
14	0.291245	2.256	0.013865
15	0.251197	1.9458	0.028186
16	0.21367	1.6551	0.051565
17	0.176276	1.3654	0.088608

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.953267	7.384	0
2	-0.018732	-0.1451	0.442561
3	-0.05151	-0.399	0.345658
4	-0.033216	-0.2573	0.398918
5	-0.031724	-0.2457	0.403362
6	-0.046315	-0.3588	0.360519
7	-0.060229	-0.4665	0.321262
8	-0.010117	-0.0784	0.468898
9	-0.025558	-0.198	0.421869
10	-0.036754	-0.2847	0.388428
11	-0.019007	-0.1472	0.441724
12	-0.036535	-0.283	0.389077
13	-0.063431	-0.4913	0.312492
14	-0.025369	-0.1965	0.422438
15	0.092009	0.7127	0.239397
16	-0.002869	-0.0222	0.491173
17	-0.037856	-0.2932	0.385179

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953267 & 7.384 & 0 \tabularnewline
2 & -0.018732 & -0.1451 & 0.442561 \tabularnewline
3 & -0.05151 & -0.399 & 0.345658 \tabularnewline
4 & -0.033216 & -0.2573 & 0.398918 \tabularnewline
5 & -0.031724 & -0.2457 & 0.403362 \tabularnewline
6 & -0.046315 & -0.3588 & 0.360519 \tabularnewline
7 & -0.060229 & -0.4665 & 0.321262 \tabularnewline
8 & -0.010117 & -0.0784 & 0.468898 \tabularnewline
9 & -0.025558 & -0.198 & 0.421869 \tabularnewline
10 & -0.036754 & -0.2847 & 0.388428 \tabularnewline
11 & -0.019007 & -0.1472 & 0.441724 \tabularnewline
12 & -0.036535 & -0.283 & 0.389077 \tabularnewline
13 & -0.063431 & -0.4913 & 0.312492 \tabularnewline
14 & -0.025369 & -0.1965 & 0.422438 \tabularnewline
15 & 0.092009 & 0.7127 & 0.239397 \tabularnewline
16 & -0.002869 & -0.0222 & 0.491173 \tabularnewline
17 & -0.037856 & -0.2932 & 0.385179 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164218&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]0.953267[/C][C]7.384[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.018732[/C][C]-0.1451[/C][C]0.442561[/C][/ROW]
[ROW][C]3[/C][C]-0.05151[/C][C]-0.399[/C][C]0.345658[/C][/ROW]
[ROW][C]4[/C][C]-0.033216[/C][C]-0.2573[/C][C]0.398918[/C][/ROW]
[ROW][C]5[/C][C]-0.031724[/C][C]-0.2457[/C][C]0.403362[/C][/ROW]
[ROW][C]6[/C][C]-0.046315[/C][C]-0.3588[/C][C]0.360519[/C][/ROW]
[ROW][C]7[/C][C]-0.060229[/C][C]-0.4665[/C][C]0.321262[/C][/ROW]
[ROW][C]8[/C][C]-0.010117[/C][C]-0.0784[/C][C]0.468898[/C][/ROW]
[ROW][C]9[/C][C]-0.025558[/C][C]-0.198[/C][C]0.421869[/C][/ROW]
[ROW][C]10[/C][C]-0.036754[/C][C]-0.2847[/C][C]0.388428[/C][/ROW]
[ROW][C]11[/C][C]-0.019007[/C][C]-0.1472[/C][C]0.441724[/C][/ROW]
[ROW][C]12[/C][C]-0.036535[/C][C]-0.283[/C][C]0.389077[/C][/ROW]
[ROW][C]13[/C][C]-0.063431[/C][C]-0.4913[/C][C]0.312492[/C][/ROW]
[ROW][C]14[/C][C]-0.025369[/C][C]-0.1965[/C][C]0.422438[/C][/ROW]
[ROW][C]15[/C][C]0.092009[/C][C]0.7127[/C][C]0.239397[/C][/ROW]
[ROW][C]16[/C][C]-0.002869[/C][C]-0.0222[/C][C]0.491173[/C][/ROW]
[ROW][C]17[/C][C]-0.037856[/C][C]-0.2932[/C][C]0.385179[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164218&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164218&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	0.953267	7.384	0
2	-0.018732	-0.1451	0.442561
3	-0.05151	-0.399	0.345658
4	-0.033216	-0.2573	0.398918
5	-0.031724	-0.2457	0.403362
6	-0.046315	-0.3588	0.360519
7	-0.060229	-0.4665	0.321262
8	-0.010117	-0.0784	0.468898
9	-0.025558	-0.198	0.421869
10	-0.036754	-0.2847	0.388428
11	-0.019007	-0.1472	0.441724
12	-0.036535	-0.283	0.389077
13	-0.063431	-0.4913	0.312492
14	-0.025369	-0.1965	0.422438
15	0.092009	0.7127	0.239397
16	-0.002869	-0.0222	0.491173
17	-0.037856	-0.2932	0.385179

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 = 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 ; 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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code