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Type 'q()' to quit R. > x <- c(655362,873127,1107897,1555964,1671159,1493308,2957796,2638691,1305669,1280496,921900,867888,652586,913831,1108544,1555827,1699283,1509458,3268975,2425016,1312703,1365498,934453,775019,651142,843192,1146766,1652601,1465906,1652734,2922334,2702805,1458956,1410363,1019279,936574,708917,885295,1099663,1576220,1487870,1488635,2882530,2677026,1404398,1344370,936865,872705,628151,953712,1160384,1400618,1661511,1495347,2918786,2775677,1407026,1370199,964526,850851,683118,847224,1073256,1514326,1503734,1507712,2865698,2788128,1391596,1366378,946295,859626) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '2' > par3 = '0' > par2 = '1' > par1 = '48' > par8 <- '' > par7 <- '0.95' > par6 <- 'White Noise' > par5 <- '12' > par4 <- '2' > par3 <- '0' > par2 <- '1' > par1 <- '48' > #'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/fisher/rcomp/tmp/19z381354644043.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/fisher/rcomp/tmp/2joai1354644043.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/fisher/rcomp/tmp/3cl941354644043.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] 1.0000000000 -0.3174977596 0.2370903678 0.0738330604 -0.0085000134 [6] 0.0875614837 -0.0942283660 -0.1679112439 -0.0217056623 -0.1056506750 [11] -0.1990215946 0.0744019846 -0.4394459388 0.1164001117 -0.1056598995 [16] 0.0012036528 0.0049192605 0.0340479609 0.2036358890 0.0233926822 [21] -0.0040047100 0.2168357176 -0.0895665027 0.1834174130 -0.0677550853 [26] -0.0126210387 0.0451598261 -0.0577147609 0.0107330640 -0.0152574815 [31] -0.1554800168 0.0564014705 0.0546102418 -0.1854116483 0.1447000942 [36] -0.1236005240 0.0807058209 0.0134144370 -0.0256559363 0.0259385765 [41] 0.0145258232 -0.0118908595 0.0105092613 -0.0080812651 0.0024656623 [46] 0.0029644717 -0.0024315665 0.0002242145 > (mypacf <- c(rpacf$acf)) [1] -0.3174977596 0.1515639147 0.2115111653 0.0374951295 0.0348302897 [6] -0.0976132575 -0.3005491033 -0.1802091123 -0.0475675472 -0.1808721639 [11] 0.0528318918 -0.3675024890 -0.2296115743 -0.0903577342 0.0309856614 [16] -0.0352511292 -0.0176444686 0.1525726270 -0.0864255260 -0.3083321115 [21] 0.0266080488 -0.2089515516 0.0575794605 -0.1641609623 -0.1566000749 [26] -0.1450217763 -0.0807182177 0.0289242447 0.0549547060 -0.0085442422 [31] -0.0502720512 -0.0790468282 -0.0696941322 -0.1133718522 0.0098198019 [36] -0.1305694087 -0.0748602227 -0.0337630177 -0.0945310041 0.0021221608 [41] 0.0363598368 -0.0680205933 -0.0103145016 0.0214197010 -0.0455516040 [46] -0.0955243229 -0.0006125924 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/46y2q1354644044.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/fisher/rcomp/tmp/5zbpo1354644044.tab") > > try(system("convert tmp/19z381354644043.ps tmp/19z381354644043.png",intern=TRUE)) character(0) > try(system("convert tmp/2joai1354644043.ps tmp/2joai1354644043.png",intern=TRUE)) character(0) > try(system("convert tmp/3cl941354644043.ps tmp/3cl941354644043.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.764 0.492 2.240