R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(630,720,740,720,720,690,790,760,840,840,640,840,590,770,750,590,730,740,770,660,830,900,630,770,640,700,760,500,740,740,680,580,780,990,630,780,630,780,730,490,710,700,740,520,730,1110,510,750,690,740,690,640,660,580,760,510,810,1050,510,740,690,800,670,670,640,540,740,600,860,1080,480,680,650,860,650,630,600,500,760,590,800,1120,520,710,600,880,700,590,680,530,730,600,880,1120,540,740,580,850,670,530,680,540,760,620,910,1230,530,720)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> par2 <- '1'
> par1 <- '48'
> #'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/19yfq1470054119.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/2s9bw1470054119.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/3v6e31470054119.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 -0.172618633 -0.093778573 -0.004753907 -0.116458866
 [6]  0.129904608 -0.366391503  0.156321426 -0.103607590 -0.048798454
[11] -0.050325849 -0.171827499  0.822345927 -0.143628005 -0.102554003
[16] -0.005170647 -0.073241417  0.086783932 -0.316311429  0.163932289
[21] -0.108496464 -0.052374102 -0.024292760 -0.155773939  0.667239067
[26] -0.123745953 -0.082038192  0.002105424 -0.037510468  0.048776560
[31] -0.275780966  0.146705514 -0.107172531 -0.042257855 -0.007006274
[36] -0.139003849  0.523805465 -0.105214188 -0.062740482 -0.016761957
[41]  0.009156207  0.040223501 -0.257864428  0.137006008 -0.102756402
[46] -0.020465880 -0.003436391 -0.097564135  0.407375150
> (mypacf <- c(rpacf$acf))
 [1] -0.1726186334 -0.1273710656 -0.0471368059 -0.1452777779  0.0780589020
 [6] -0.3856935749  0.0556907228 -0.2430160966 -0.0777481922 -0.3240432471
[11] -0.2616536681  0.7157573409  0.0496709008  0.0176752443 -0.1219542092
[16]  0.1223836582 -0.1042591664  0.1347034154 -0.0727255290 -0.0221142060
[21] -0.0012670930  0.0317227127 -0.0214070474 -0.0257099710 -0.0224393554
[26]  0.0221688102  0.0564926742  0.0100973989 -0.0429704195 -0.0107239176
[31] -0.0746629867  0.0025653666  0.0145790393 -0.0006874299 -0.0458415452
[36] -0.0529813415 -0.0283728063 -0.0244998759 -0.0779531680  0.0183710365
[41]  0.0285616028 -0.0528294125 -0.0161171241 -0.0321099954  0.0210737773
[46] -0.0497536740  0.1013079125 -0.0676269064
> 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/49l7m1470054119.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/51lcn1470054119.tab") 
> 
> try(system("convert tmp/19yfq1470054119.ps tmp/19yfq1470054119.png",intern=TRUE))
character(0)
> try(system("convert tmp/2s9bw1470054119.ps tmp/2s9bw1470054119.png",intern=TRUE))
character(0)
> try(system("convert tmp/3v6e31470054119.ps tmp/3v6e31470054119.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.382   0.146   1.569