R version 3.0.2 (2013-09-25) -- "Frisbee Sailing" Copyright (C) 2013 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(96.01,96.39,97.16,97.46,97.6,97.02,96.95,97.23,98,98.04,97.76,96.99,97.44,98,98.84,98.98,98.92,98.63,98.52,98.97,99.74,99.68,99.45,98.97,98.68,99.06,99.84,100.3,100.38,100.02,99.83,100.36,100.74,100.49,100.33,99.96,100.08,100.54,101.63,102.12,102.19,101.77,101.29,101.47,102.07,102.11,102.26,101.83,102.11,102.8,103.82,104.2,104.57,104.38,104.54,104.74,105.19,104.95,104.57,103.81,104.08,104.81,105.86,106.1,106.24,105.87,104.74,105.03,105.59,105.69,105.58,104.96,104.93,105.68,106.93,107.29,107.25,106.74,106.44,106.6,107.26,107.35,107.22,106.99,107,107.74,109.02,109.54,109.71,109.18,109.23,109.38,110.17,110.15,110.01,109.54,109.52,110.35,111.61,112.06,111.9,111.36,112.09,112.24,112.7,113.36,112.9,112.74,112.77,113.66,114.87,114.97,115,114.57,115.54,115.39,115.46,115.13,114.56,114.62) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '1' > par2 = '1' > par1 = '48' > par8 <- '' > par7 <- '0.95' > par6 <- 'White Noise' > par5 <- '12' > par4 <- '0' > par3 <- '1' > 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/wessaorg/rcomp/tmp/13mar1425305680.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/2ibww1425305680.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/3sddy1425305680.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] 1.00000000 0.34287877 -0.22838242 -0.63354505 -0.31171816 0.22268918 [7] 0.50160857 0.15633515 -0.35646069 -0.58414993 -0.17613846 0.33995367 [13] 0.72819088 0.27313664 -0.24761787 -0.54395194 -0.26151321 0.18235607 [19] 0.45018419 0.10914647 -0.35070861 -0.53097269 -0.13269452 0.31686753 [25] 0.62013842 0.24860297 -0.20854540 -0.48375779 -0.21925554 0.15428628 [31] 0.36774043 0.06517289 -0.29113348 -0.43996702 -0.09615674 0.27495244 [37] 0.51100212 0.23174887 -0.16879700 -0.45506612 -0.15115392 0.12751556 [43] 0.35581648 0.03830040 -0.24662674 -0.36650484 -0.09885315 0.24039709 [49] 0.41713412 > (mypacf <- c(rpacf$acf)) [1] 0.34287877 -0.39203862 -0.52237755 0.01371662 0.17652421 0.07356892 [7] -0.23096198 -0.26648417 -0.23433852 0.02751214 0.02527709 0.41587329 [13] 0.01124682 0.01897857 0.04071412 -0.08217816 -0.16513292 0.02887064 [19] -0.08617387 -0.12759702 -0.05494832 0.02852204 -0.08919907 0.06678157 [25] 0.05912989 0.06198461 -0.04629236 -0.02015194 -0.07218508 -0.11523415 [31] -0.11090025 0.03722345 -0.01378114 -0.02241828 -0.01968456 -0.00765920 [37] 0.01911402 -0.01577231 -0.18737227 0.12595646 -0.05668679 0.03096806 [43] -0.08151440 0.03718462 0.07733395 -0.11942143 -0.07443671 -0.03271641 > 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/405401425305680.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/5rdhg1425305680.tab") > > try(system("convert tmp/13mar1425305680.ps tmp/13mar1425305680.png",intern=TRUE)) character(0) > try(system("convert tmp/2ibww1425305680.ps tmp/2ibww1425305680.png",intern=TRUE)) character(0) > try(system("convert tmp/3sddy1425305680.ps tmp/3sddy1425305680.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.192 0.242 1.448