| PaperTimDamen | *Unverified author* | R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values) | Title produced by software: (Partial) Autocorrelation Function | Date of computation: Mon, 31 Jan 2011 10:36:52 +0000 | | Cite this page as follows: | Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp.htm/, Retrieved Mon, 31 Jan 2011 11:36:49 +0100 | | BibTeX entries for LaTeX users: | @Manual{KEY,
author = {{YOUR NAME}},
publisher = {Office for Research Development and Education},
title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp.htm/},
year = {2011},
}
@Manual{R,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Development Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2011},
note = {{ISBN} 3-900051-07-0},
url = {http://www.R-project.org},
}
| | Original text written by user: | | | IsPrivate? | No (this computation is public) | | User-defined keywords: | | | Dataseries X: | » Textbox « » Textfile « » CSV « | 349
336
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385
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589
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508
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488
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570
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563
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606
606
595
595
599
599
600
600
592
592
575
575
567
567
555
555
555
555
608
etc... | | Output produced by software: |
Autocorrelation Function | Time lag k | ACF(k) | T-STAT | P-value | 1 | 0.959754 | 21.2884 | 0 | 2 | 0.905836 | 20.0924 | 0 | 3 | 0.849051 | 18.8329 | 0 | 4 | 0.801148 | 17.7703 | 0 | 5 | 0.766859 | 17.0098 | 0 | 6 | 0.73339 | 16.2674 | 0 | 7 | 0.70983 | 15.7448 | 0 | 8 | 0.688748 | 15.2772 | 0 | 9 | 0.682133 | 15.1304 | 0 | 10 | 0.684046 | 15.1729 | 0 | 11 | 0.691235 | 15.3323 | 0 | 12 | 0.687781 | 15.2557 | 0 | 13 | 0.645231 | 14.3119 | 0 | 14 | 0.592879 | 13.1507 | 0 | 15 | 0.545826 | 12.107 | 0 | 16 | 0.508655 | 11.2825 | 0 | 17 | 0.484402 | 10.7446 | 0 | 18 | 0.461311 | 10.2324 | 0 | 19 | 0.44554 | 9.8826 | 0 | 20 | 0.432848 | 9.601 | 0 | 21 | 0.433381 | 9.6128 | 0 | 22 | 0.442292 | 9.8105 | 0 | 23 | 0.451172 | 10.0075 | 0 | 24 | 0.451299 | 10.0103 | 0 | 25 | 0.402558 | 8.9292 | 0 | 26 | 0.345948 | 7.6735 | 0 |
Partial Autocorrelation Function | Time lag k | PACF(k) | T-STAT | P-value | 1 | 0.959754 | 21.2884 | 0 | 2 | -0.193891 | -4.3007 | 1e-05 | 3 | -0.036957 | -0.8197 | 0.206379 | 4 | 0.093617 | 2.0765 | 0.019182 | 5 | 0.115143 | 2.554 | 0.005475 | 6 | -0.06915 | -1.5338 | 0.06286 | 7 | 0.11944 | 2.6493 | 0.004162 | 8 | 0.00939 | 0.2083 | 0.417552 | 9 | 0.183814 | 4.0772 | 2.7e-05 | 10 | 0.063709 | 1.4131 | 0.079125 | 11 | 0.081301 | 1.8034 | 0.035972 | 12 | -0.138191 | -3.0652 | 0.001147 | 13 | -0.426844 | -9.4679 | 0 | 14 | 0.01169 | 0.2593 | 0.397759 | 15 | 0.169186 | 3.7527 | 9.8e-05 | 16 | 0.004771 | 0.1058 | 0.457879 | 17 | 0.048342 | 1.0723 | 0.142061 | 18 | -0.008145 | -0.1807 | 0.428349 | 19 | 0.047956 | 1.0637 | 0.143988 | 20 | -0.000647 | -0.0143 | 0.49428 | 21 | 0.083893 | 1.8608 | 0.031682 | 22 | 0.012537 | 0.2781 | 0.390535 | 23 | -0.059155 | -1.3121 | 0.095045 | 24 | -0.005122 | -0.1136 | 0.454794 | 25 | -0.44914 | -9.9624 | 0 | 26 | 0.070337 | 1.5601 | 0.059684 |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp/1dt3k1296470211.png (open in new window) | http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp/1dt3k1296470211.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp/2fa451296470211.png (open in new window) | http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp/2fa451296470211.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp/307yg1296470211.png (open in new window) | http://www.freestatistics.org/blog/date/2011/Jan/31/t12964702061ar7vpammqy3wkp/307yg1296470211.ps (open in new window) |
| | 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 ; | | 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('http://www.xycoon.com/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('http://www.xycoon.com/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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This work is licensed under a
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