R version 3.3.3 (2017-03-06) -- "Another Canoe"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(3.65,3.66,3.36,3.19,2.81,2.25,2.32,2.85,2.75,2.78,2.26,2.23,1.46,1.19,1.11,1,1.18,1.59,1.51,1.01,0.9,0.63,0.81,0.97,1.14,0.97,0.89,0.62,0.36,0.27,0.34,0.02,-0.12,0.09,-0.11,-0.38,-0.65,-0.4,-0.4,0.29,0.56,0.63,0.46,0.91,1.06,1.28,1.52,1.5,1.74,1.39,2.24,2.04,2.2,2.16,2.28,2.16,1.87,1.81,1.77,2.03,2.65)
> 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/1rqbs1489834337.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/2k8hv1489834337.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/3xevo1489834337.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  0.908350464  0.818456613  0.728968975  0.655274659
 [6]  0.594601527  0.556015769  0.503287005  0.410653164  0.314692786
[11]  0.206754125  0.102984758  0.015415000 -0.030258286 -0.064964362
[16] -0.093007113 -0.124756955 -0.167975193 -0.235238577 -0.278182810
[21] -0.301214741 -0.319904934 -0.331085851 -0.344315014 -0.372674266
[26] -0.401665168 -0.419174597 -0.444525459 -0.457061035 -0.454165750
[31] -0.439715430 -0.440885324 -0.419793088 -0.394971985 -0.376879782
[36] -0.348510588 -0.299492909 -0.243812128 -0.198093777 -0.137012946
[41] -0.093724156 -0.048960813 -0.002464029  0.047533581  0.070008027
[46]  0.091531227  0.112865736  0.126763010  0.144649514
> (mypacf <- c(rpacf$acf))
 [1]  0.908350464 -0.037987274 -0.047021563  0.038912312  0.031073079
 [6]  0.088597969 -0.101174063 -0.260318148 -0.067963532 -0.136568655
[11] -0.094676046 -0.042887957  0.115819986  0.048721254  0.045133309
[16] -0.004296724 -0.038011034 -0.162248969  0.027620055 -0.030883689
[21] -0.106591816 -0.078609663 -0.083821652 -0.089831318  0.020442000
[26] -0.002917523 -0.094876158  0.001271308  0.013173687  0.003759681
[31] -0.102123220  0.086495379  0.029351203 -0.050674961  0.006868440
[36]  0.037250070  0.039051020 -0.027590536  0.032466994 -0.066523689
[41]  0.036123139  0.001361284 -0.027191225 -0.123771508 -0.035924195
[46] -0.026501977 -0.007782581  0.054593953
> 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/45axx1489834337.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/5n2wr1489834337.tab") 
> 
> try(system("convert tmp/1rqbs1489834337.ps tmp/1rqbs1489834337.png",intern=TRUE))
character(0)
> try(system("convert tmp/2k8hv1489834337.ps tmp/2k8hv1489834337.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xevo1489834337.ps tmp/3xevo1489834337.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.209   0.102   1.327