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(40927.00
+ ,40856.00
+ ,40778.00
+ ,40635.00
+ ,42103.00
+ ,42032.00
+ ,40927.00
+ ,40194.00
+ ,40265.00
+ ,40265.00
+ ,40336.00
+ ,40486.00
+ ,40856.00
+ ,40414.00
+ ,40856.00
+ ,40486.00
+ ,41661.00
+ ,42181.00
+ ,39973.00
+ ,39381.00
+ ,39894.00
+ ,39823.00
+ ,39381.00
+ ,39453.00
+ ,40336.00
+ ,40194.00
+ ,40336.00
+ ,40336.00
+ ,41298.00
+ ,41440.00
+ ,38790.00
+ ,38790.00
+ ,39823.00
+ ,39310.00
+ ,38427.00
+ ,38790.00
+ ,39674.00
+ ,39232.00
+ ,39161.00
+ ,38206.00
+ ,39602.00
+ ,39894.00
+ ,37023.00
+ ,36952.00
+ ,38427.00
+ ,37615.00
+ ,36218.00
+ ,36810.00
+ ,37465.00
+ ,37615.00
+ ,37173.00
+ ,36290.00
+ ,38128.00
+ ,38128.00
+ ,34893.00
+ ,34673.00
+ ,35556.00
+ ,33939.00
+ ,32314.00
+ ,32835.00
+ ,33939.00
+ ,33055.00
+ ,32464.00
+ ,31210.00
+ ,32906.00
+ ,32977.00
+ ,29743.00
+ ,29664.00
+ ,30256.00
+ ,28418.00
+ ,26430.00
+ ,27235.00
+ ,28339.00
+ ,27164.00
+ ,27093.00
+ ,25910.00
+ ,27826.00
+ ,28197.00
+ ,24585.00
+ ,23780.00
+ ,24293.00
+ ,22305.00
+ ,20246.00
+ ,20909.00
+ ,22156.00
+ ,20688.00
+ ,20909.00
+ ,20026.00
+ ,21864.00
+ ,22084.00
+ ,17668.00
+ ,17375.00
+ ,18180.00
+ ,16050.00
+ ,14134.00
+ ,14797.00
+ ,16414.00
+ ,14504.00
+ ,14355.00
+ ,12880.00
+ ,14504.00
+ ,15017.00
+ ,10451.00
+ ,10451.00
+ ,11113.00
+ ,9347.00
+ ,7359.00
+ ,8392.00
+ ,10230.00
+ ,8242.00
+ ,9055.00
+ ,7950.00
+ ,9717.00
+ ,10308.00
+ ,5592.00
+ ,5229.00
+ ,5963.00
+ ,4196.00
+ ,2800.00
+ ,3384.00)
> 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/108w01470928614.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/2z8j21470928614.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/3d6sx1470928614.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  0.970504258  0.941070334  0.919919162  0.897951532
 [6]  0.868975281  0.840660270  0.824634979  0.808242215  0.784392232
[11]  0.759197259  0.738479184  0.720988413  0.688780888  0.656217804
[16]  0.632140196  0.607470107  0.576268121  0.545226406  0.526410846
[21]  0.507028112  0.480531816  0.453875784  0.432654016  0.414354023
[26]  0.383047243  0.351635864  0.328220235  0.304648240  0.275148872
[31]  0.246910069  0.230451122  0.213329727  0.189150131  0.164917399
[36]  0.145128619  0.127298467  0.098766691  0.070348327  0.049511698
[41]  0.029273803  0.003793266 -0.019538789 -0.032627574 -0.046780290
[46] -0.067601508 -0.087303069 -0.102399465 -0.116014495
> (mypacf <- c(rpacf$acf))
 [1]  0.9705042584 -0.0139050461  0.1273724686 -0.0255188848 -0.1143568922
 [6] -0.0072625026  0.1726932510 -0.0110693686 -0.0850679865 -0.0462974798
[11]  0.0059074340  0.0491740849 -0.2131355293 -0.0130802810  0.0472989722
[16] -0.0370363131 -0.0577347124 -0.0029769795  0.0993652199 -0.0276020100
[21] -0.0432250651 -0.0205985497  0.0073980938  0.0224584086 -0.1368978984
[26] -0.0071545810  0.0099714285 -0.0287910165 -0.0349032906  0.0235000650
[31]  0.0611951081 -0.0300908491 -0.0325930781 -0.0239793442 -0.0193149031
[36] -0.0010547518 -0.0786591552 -0.0107013353 -0.0063145672 -0.0164178433
[41] -0.0232492393  0.0368767745  0.0225835301 -0.0334312226 -0.0250302002
[46] -0.0053982891 -0.0129193534  0.0002217489
> 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/4cakj1470928614.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/5co901470928614.tab") 
> 
> try(system("convert tmp/108w01470928614.ps tmp/108w01470928614.png",intern=TRUE))
character(0)
> try(system("convert tmp/2z8j21470928614.ps tmp/2z8j21470928614.png",intern=TRUE))
character(0)
> try(system("convert tmp/3d6sx1470928614.ps tmp/3d6sx1470928614.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.368   0.126   1.510