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Type 'q()' to quit R. > x <- c(20.7,20.4,20.3,20.4,19.8,19.5,23.1,23.5,23.5,22.9,21.9,21.5,20.5,20.2,19.4,19.2,18.8,18.8,22.6,23.3,23,21.4,19.9,18.8,18.6,18.4,18.6,19.9,19.2,18.4,21.1,20.5,19.1,18.1,17,17.1,17.4,16.8,15.3,14.3,13.4,15.3,22.1,23.7,22.2,19.5,16.6,17.3,19.8,21.2,21.5,20.6,19.1,19.6,23.4,24.3,24.1,22.8,22.5,23.8,24.9,25.2,24.3,22.8,20.7,19.8,22.5,22.6,22.5,21.8,21.2,20.6,19.9,18.7,17.6,16.4,15.9,16.8,22.8,24,22.2,17.9,16,16) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '0' > par2 = '1' > par1 = '60' > par8 <- '' > par7 <- '0.95' > par6 <- 'White Noise' > par5 <- '12' > par4 <- '0' > par3 <- '0' > par2 <- '1' > par1 <- '60' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) 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) > 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/1pck11352997639.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/2983r1352997639.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/3z9d51352997639.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 0.775709664 0.397825763 0.124825916 0.076301124 [6] 0.193696205 0.296658365 0.252113747 0.136600015 0.064249555 [11] 0.082670906 0.174070218 0.213013102 0.037145271 -0.172222102 [16] -0.283971676 -0.275086678 -0.201369453 -0.180184719 -0.276748662 [21] -0.397568074 -0.432534760 -0.350813579 -0.185583599 -0.073287513 [26] -0.161996987 -0.296369841 -0.351033142 -0.303501132 -0.207076655 [31] -0.165576464 -0.221771756 -0.279211017 -0.230635840 -0.066565451 [36] 0.143970114 0.258163896 0.149791273 -0.015804129 -0.091118574 [41] -0.044822418 0.075360995 0.156797197 0.130264268 0.063541992 [46] 0.028788889 0.052771286 0.132180790 0.202518629 0.181550805 [51] 0.139158843 0.110922531 0.095980441 0.082601172 0.054944352 [56] 0.009840931 -0.007002507 0.016863871 0.065024255 0.115802188 [61] 0.131074976 > (mypacf <- c(rpacf$acf)) [1] 0.775709664 -0.511957737 0.188407516 0.223276721 0.132602081 [6] -0.065581660 -0.126142486 0.147260664 0.064990151 0.005100918 [11] 0.087004102 -0.107146552 -0.463284230 0.279695993 -0.113436795 [16] -0.256361812 -0.083773273 -0.078171296 -0.164167216 -0.137914409 [21] 0.072554409 0.070798405 -0.029677815 -0.025007918 -0.064729910 [26] 0.115321436 -0.016536283 -0.079201935 -0.070934317 -0.079012307 [31] -0.072864450 -0.047274242 0.102739403 0.083135159 -0.057218517 [36] 0.000618419 -0.074074203 -0.005047381 -0.045802380 -0.076152987 [41] 0.016870646 -0.036093206 -0.089471753 -0.025354577 -0.166204629 [46] -0.110586177 -0.020705546 0.063778101 0.132656327 -0.093181490 [51] -0.097300310 0.063765358 -0.080890881 0.030400385 0.097644882 [56] -0.015337995 -0.081095154 -0.030208525 -0.022823522 -0.026313949 > 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/42axg1352997639.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/58vv61352997639.tab") > > try(system("convert tmp/1pck11352997639.ps tmp/1pck11352997639.png",intern=TRUE)) character(0) > try(system("convert tmp/2983r1352997639.ps tmp/2983r1352997639.png",intern=TRUE)) character(0) > try(system("convert tmp/3z9d51352997639.ps tmp/3z9d51352997639.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.108 0.412 2.542