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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 04 Dec 2009 05:08:40 -0700

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/2009/Dec/04/t1259928565b3xg4nxufve1keo.htm/, Retrieved Sat, 27 Apr 2024 23:48:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63355, Retrieved Sat, 27 Apr 2024 23:48:47 +0000

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Estimated Impact

119

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:48:46] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [] [2009-12-04 12:08:40] [1c773da0103d9327c2f1f790e2d74438] [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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63355&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63355&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63355&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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.366049	2.5095	0.007797
2	0.135699	0.9303	0.178483
3	0.088051	0.6036	0.27449
4	0.178749	1.2254	0.113258
5	0.169262	1.1604	0.125873
6	-0.027623	-0.1894	0.425308
7	-0.229585	-1.574	0.061103
8	-0.122733	-0.8414	0.202188
9	-0.068389	-0.4689	0.320671
10	-0.127552	-0.8745	0.19316
11	-0.238482	-1.635	0.05437
12	-0.438343	-3.0051	0.002124
13	-0.210818	-1.4453	0.077505
14	-0.044201	-0.303	0.381604
15	0.053874	0.3693	0.356767
16	-0.005193	-0.0356	0.485876
17	0.086894	0.5957	0.277111

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.366049 & 2.5095 & 0.007797 \tabularnewline
2 & 0.135699 & 0.9303 & 0.178483 \tabularnewline
3 & 0.088051 & 0.6036 & 0.27449 \tabularnewline
4 & 0.178749 & 1.2254 & 0.113258 \tabularnewline
5 & 0.169262 & 1.1604 & 0.125873 \tabularnewline
6 & -0.027623 & -0.1894 & 0.425308 \tabularnewline
7 & -0.229585 & -1.574 & 0.061103 \tabularnewline
8 & -0.122733 & -0.8414 & 0.202188 \tabularnewline
9 & -0.068389 & -0.4689 & 0.320671 \tabularnewline
10 & -0.127552 & -0.8745 & 0.19316 \tabularnewline
11 & -0.238482 & -1.635 & 0.05437 \tabularnewline
12 & -0.438343 & -3.0051 & 0.002124 \tabularnewline
13 & -0.210818 & -1.4453 & 0.077505 \tabularnewline
14 & -0.044201 & -0.303 & 0.381604 \tabularnewline
15 & 0.053874 & 0.3693 & 0.356767 \tabularnewline
16 & -0.005193 & -0.0356 & 0.485876 \tabularnewline
17 & 0.086894 & 0.5957 & 0.277111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63355&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]0.366049[/C][C]2.5095[/C][C]0.007797[/C][/ROW]
[ROW][C]2[/C][C]0.135699[/C][C]0.9303[/C][C]0.178483[/C][/ROW]
[ROW][C]3[/C][C]0.088051[/C][C]0.6036[/C][C]0.27449[/C][/ROW]
[ROW][C]4[/C][C]0.178749[/C][C]1.2254[/C][C]0.113258[/C][/ROW]
[ROW][C]5[/C][C]0.169262[/C][C]1.1604[/C][C]0.125873[/C][/ROW]
[ROW][C]6[/C][C]-0.027623[/C][C]-0.1894[/C][C]0.425308[/C][/ROW]
[ROW][C]7[/C][C]-0.229585[/C][C]-1.574[/C][C]0.061103[/C][/ROW]
[ROW][C]8[/C][C]-0.122733[/C][C]-0.8414[/C][C]0.202188[/C][/ROW]
[ROW][C]9[/C][C]-0.068389[/C][C]-0.4689[/C][C]0.320671[/C][/ROW]
[ROW][C]10[/C][C]-0.127552[/C][C]-0.8745[/C][C]0.19316[/C][/ROW]
[ROW][C]11[/C][C]-0.238482[/C][C]-1.635[/C][C]0.05437[/C][/ROW]
[ROW][C]12[/C][C]-0.438343[/C][C]-3.0051[/C][C]0.002124[/C][/ROW]
[ROW][C]13[/C][C]-0.210818[/C][C]-1.4453[/C][C]0.077505[/C][/ROW]
[ROW][C]14[/C][C]-0.044201[/C][C]-0.303[/C][C]0.381604[/C][/ROW]
[ROW][C]15[/C][C]0.053874[/C][C]0.3693[/C][C]0.356767[/C][/ROW]
[ROW][C]16[/C][C]-0.005193[/C][C]-0.0356[/C][C]0.485876[/C][/ROW]
[ROW][C]17[/C][C]0.086894[/C][C]0.5957[/C][C]0.277111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63355&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63355&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	0.366049	2.5095	0.007797
2	0.135699	0.9303	0.178483
3	0.088051	0.6036	0.27449
4	0.178749	1.2254	0.113258
5	0.169262	1.1604	0.125873
6	-0.027623	-0.1894	0.425308
7	-0.229585	-1.574	0.061103
8	-0.122733	-0.8414	0.202188
9	-0.068389	-0.4689	0.320671
10	-0.127552	-0.8745	0.19316
11	-0.238482	-1.635	0.05437
12	-0.438343	-3.0051	0.002124
13	-0.210818	-1.4453	0.077505
14	-0.044201	-0.303	0.381604
15	0.053874	0.3693	0.356767
16	-0.005193	-0.0356	0.485876
17	0.086894	0.5957	0.277111

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.366049	2.5095	0.007797
2	0.001971	0.0135	0.494637
3	0.043596	0.2989	0.383174
4	0.153321	1.0511	0.14929
5	0.061337	0.4205	0.338016
6	-0.147456	-1.0109	0.158619
7	-0.23275	-1.5957	0.058635
8	0.014012	0.0961	0.461939
9	-0.036659	-0.2513	0.401332
10	-0.094489	-0.6478	0.260139
11	-0.105056	-0.7202	0.237475
12	-0.316507	-2.1699	0.017553
13	0.033878	0.2323	0.408673
14	0.051282	0.3516	0.363366
15	0.161043	1.1041	0.137595
16	0.067999	0.4662	0.321621
17	0.17207	1.1797	0.122037

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.366049 & 2.5095 & 0.007797 \tabularnewline
2 & 0.001971 & 0.0135 & 0.494637 \tabularnewline
3 & 0.043596 & 0.2989 & 0.383174 \tabularnewline
4 & 0.153321 & 1.0511 & 0.14929 \tabularnewline
5 & 0.061337 & 0.4205 & 0.338016 \tabularnewline
6 & -0.147456 & -1.0109 & 0.158619 \tabularnewline
7 & -0.23275 & -1.5957 & 0.058635 \tabularnewline
8 & 0.014012 & 0.0961 & 0.461939 \tabularnewline
9 & -0.036659 & -0.2513 & 0.401332 \tabularnewline
10 & -0.094489 & -0.6478 & 0.260139 \tabularnewline
11 & -0.105056 & -0.7202 & 0.237475 \tabularnewline
12 & -0.316507 & -2.1699 & 0.017553 \tabularnewline
13 & 0.033878 & 0.2323 & 0.408673 \tabularnewline
14 & 0.051282 & 0.3516 & 0.363366 \tabularnewline
15 & 0.161043 & 1.1041 & 0.137595 \tabularnewline
16 & 0.067999 & 0.4662 & 0.321621 \tabularnewline
17 & 0.17207 & 1.1797 & 0.122037 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63355&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]0.366049[/C][C]2.5095[/C][C]0.007797[/C][/ROW]
[ROW][C]2[/C][C]0.001971[/C][C]0.0135[/C][C]0.494637[/C][/ROW]
[ROW][C]3[/C][C]0.043596[/C][C]0.2989[/C][C]0.383174[/C][/ROW]
[ROW][C]4[/C][C]0.153321[/C][C]1.0511[/C][C]0.14929[/C][/ROW]
[ROW][C]5[/C][C]0.061337[/C][C]0.4205[/C][C]0.338016[/C][/ROW]
[ROW][C]6[/C][C]-0.147456[/C][C]-1.0109[/C][C]0.158619[/C][/ROW]
[ROW][C]7[/C][C]-0.23275[/C][C]-1.5957[/C][C]0.058635[/C][/ROW]
[ROW][C]8[/C][C]0.014012[/C][C]0.0961[/C][C]0.461939[/C][/ROW]
[ROW][C]9[/C][C]-0.036659[/C][C]-0.2513[/C][C]0.401332[/C][/ROW]
[ROW][C]10[/C][C]-0.094489[/C][C]-0.6478[/C][C]0.260139[/C][/ROW]
[ROW][C]11[/C][C]-0.105056[/C][C]-0.7202[/C][C]0.237475[/C][/ROW]
[ROW][C]12[/C][C]-0.316507[/C][C]-2.1699[/C][C]0.017553[/C][/ROW]
[ROW][C]13[/C][C]0.033878[/C][C]0.2323[/C][C]0.408673[/C][/ROW]
[ROW][C]14[/C][C]0.051282[/C][C]0.3516[/C][C]0.363366[/C][/ROW]
[ROW][C]15[/C][C]0.161043[/C][C]1.1041[/C][C]0.137595[/C][/ROW]
[ROW][C]16[/C][C]0.067999[/C][C]0.4662[/C][C]0.321621[/C][/ROW]
[ROW][C]17[/C][C]0.17207[/C][C]1.1797[/C][C]0.122037[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63355&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63355&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	0.366049	2.5095	0.007797
2	0.001971	0.0135	0.494637
3	0.043596	0.2989	0.383174
4	0.153321	1.0511	0.14929
5	0.061337	0.4205	0.338016
6	-0.147456	-1.0109	0.158619
7	-0.23275	-1.5957	0.058635
8	0.014012	0.0961	0.461939
9	-0.036659	-0.2513	0.401332
10	-0.094489	-0.6478	0.260139
11	-0.105056	-0.7202	0.237475
12	-0.316507	-2.1699	0.017553
13	0.033878	0.2323	0.408673
14	0.051282	0.3516	0.363366
15	0.161043	1.1041	0.137595
16	0.067999	0.4662	0.321621
17	0.17207	1.1797	0.122037

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code