R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(90.36,90.67,91.21,91.35,91.62,91.28,91.17,91.13,91.55,91.62,91.73,91.91,92.5,92.93,92.77,93.42,93.82,94.02,94.13,93.7,93.84,94.22,95.03,95.03,95.25,96.11,96.16,96.1,96.52,96.35,96.35,96.66,96.86,97.84,98.04,98.06,98.79,99.38,99.75,100.4,100.97,101.16,100.42,99.88,99.8,99.78,99.78,99.89,100.38,100.1,100.02,101.15,100.02,99.99,100.14,98.93,98.52,98.42,98.78,99.04,99.53,99.97,99.95,101.68,101.29,101.45,100.98,100.64,100.6,101.59,101.15,101.03)
> 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/1mbfn1489660949.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/21m1z1489660949.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/3tb371489660949.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  0.957324672  0.914635363  0.871693263  0.829905603
 [6]  0.790270758  0.746731033  0.698753778  0.651514633  0.606464058
[11]  0.567230074  0.525799368  0.486069497  0.446817066  0.409724026
[16]  0.371393174  0.334071664  0.299122349  0.262085622  0.224286491
[21]  0.185379639  0.142485554  0.106393195  0.075015254  0.038227920
[26]  0.001948718 -0.030204877 -0.064821145 -0.099575407 -0.132115189
[31] -0.170509704 -0.212413877 -0.250248275 -0.285033802 -0.310036193
[36] -0.330081908 -0.349065875 -0.362604941 -0.372140215 -0.381292987
[41] -0.381451873 -0.374672240 -0.365828372 -0.361250344 -0.361389779
[46] -0.359562124 -0.358246306 -0.356958252 -0.353326189
> (mypacf <- c(rpacf$acf))
 [1]  0.957324672 -0.021970261 -0.025324116 -0.009106080  0.002967134
 [6] -0.069087911 -0.078311298 -0.018519433 -0.002337188  0.038587410
[11] -0.052297476 -0.001532639 -0.015766500 -0.001301669 -0.051074684
[16] -0.019273197  0.004189887 -0.052279943 -0.039926772 -0.046765805
[21] -0.075084772  0.042135908  0.026298590 -0.099304504 -0.024123362
[26]  0.029308752 -0.070651035 -0.058834410 -0.011152159 -0.104854373
[31] -0.088127685 -0.001515046 -0.016890539  0.074368026  0.037106645
[36] -0.022717725  0.032732651  0.032412811 -0.051490176  0.056888053
[41]  0.078576083 -0.002181141 -0.072513112 -0.055906836 -0.002483531
[46] -0.049606877 -0.010465141  0.014411220
> 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/44g4u1489660949.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/53vky1489660949.tab") 
> 
> try(system("convert tmp/1mbfn1489660949.ps tmp/1mbfn1489660949.png",intern=TRUE))
character(0)
> try(system("convert tmp/21m1z1489660949.ps tmp/21m1z1489660949.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tb371489660949.ps tmp/3tb371489660949.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.465   0.112   1.611