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Type 'q()' to quit R. > x <- c(84.97,85.57,85.74,85.88,85.88,85.96,85.96,85.99,86.02,86.14,86.3,86.32,86.32,86.77,87.47,87.39,87.3,87.31,87.31,87.38,87.4,87.32,87.37,87.4,87.4,87.89,87.7,87.89,88.02,88.08,88.08,88.15,88.21,88.41,88.39,88.41,88.41,89.1,90.35,90.61,91.18,91.22,91.22,91.4,91.52,91.68,91.71,91.77,91.77,92.16,93.64,93.78,93.96,93.82,93.82,93.89,94.05,94.46,94.62,94.72,94.72,95.76,96.14,97.11,97.19,97.43,97.43,97.56,97.66,97.75,97.82,97.82,97.82,98.35,98.19,98.19,98.21,98.22,98.26,98.23,98.26,98.5,98.51,98.51,98.51,98.89,99.55,99.9,100.12,100.09,100.09,100.09,100.46,100.71,100.79,100.79,100.93,101.15,101.53,101.91,102.18,102.24,102.2,102.32,102.43,102.45,102.84,102.96,102.96,103.1,103.4,103.74,103.97,104.29,104.33,104.46,104.9,105.31,105.63,105.68) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '1' > par2 = '1' > par1 = 'Default' > par8 <- '' > par7 <- '0.95' > par6 <- 'White Noise' > par5 <- '12' > par4 <- '0' > par3 <- '1' > par2 <- '1' > par1 <- 'Default' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000) > #Author: root > #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/ > #Source of accompanying publication: > # > 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) > postscript(file="/var/wessaorg/rcomp/tmp/1v1oo1457711122.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > 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() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2ho7g1457711122.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3s9kg1457711122.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub) > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.000000000 0.216148416 0.071792015 -0.170871805 -0.101322161 [6] -0.003879850 0.028083443 -0.004599162 -0.138258755 -0.174689631 [11] -0.032568749 0.174848858 0.343116286 0.273176482 -0.077125598 [16] -0.145583607 -0.204179566 -0.120084787 -0.034696445 -0.032425193 [21] -0.087098270 > (mypacf <- c(rpacf$acf)) [1] 0.216148416 0.026300648 -0.201198968 -0.028329785 0.054301030 [6] -0.006307742 -0.043765055 -0.138541241 -0.116699051 0.050439445 [11] 0.168205022 0.242703849 0.155214335 -0.174140140 -0.069093006 [16] -0.104380204 -0.140206526 -0.045823298 -0.006857839 -0.002197184 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/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="/var/wessaorg/rcomp/tmp/4q16l1457711122.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="/var/wessaorg/rcomp/tmp/5pxim1457711122.tab") > > try(system("convert tmp/1v1oo1457711122.ps tmp/1v1oo1457711122.png",intern=TRUE)) character(0) > try(system("convert tmp/2ho7g1457711122.ps tmp/2ho7g1457711122.png",intern=TRUE)) character(0) > try(system("convert tmp/3s9kg1457711122.ps tmp/3s9kg1457711122.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.345 0.219 1.574