R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(3.875,3.863,3.876,3.878,3.881,3.883,3.884,3.885,3.895,3.903,3.911,3.929,3.946,3.965,3.992,4.010,4.015,4.020,4.037,4.059,4.083,4.102,4.126,4.145,4.162,4.169,4.178,4.174,4.168,4.170,4.159,4.159,4.143,4.159,4.167,4.176,4.185,4.195,4.210,4.226,4.250,4.259,4.270,4.277,4.286,4.303,4.320,4.336,4.352,4.371,4.392,4.415,4.442,4.457,4.472,4.474,4.461,4.453,4.446,4.450,4.459,4.474,4.492,4.509,4.526,4.541,4.550,4.562,4.555,4.554,4.551,4.553)
> par2 = '12'
> par1 = 'additive'
> par2 <- as.numeric(par2)
> x <- ts(x,freq=par2)
> m <- decompose(x,type=par1)
> m$figure
 [1] -0.0040381944 -0.0012298611  0.0056284722  0.0087034722  0.0113451389
 [6]  0.0100118056  0.0026618056 -0.0008965278 -0.0083215278 -0.0083131944
[11] -0.0089465278 -0.0066048611
> postscript(file="/var/fisher/rcomp/tmp/1xlwt1386251467.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m)
> dev.off()
null device 
          1 
> mylagmax <- length(x)/2
> postscript(file="/var/fisher/rcomp/tmp/25pd41386251467.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
> acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
> acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/32amk1386251467.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
> spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
> spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/449ze1386251467.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
> cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
> cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
> par(op)
> dev.off()
null device 
          1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observations',header=TRUE)
> a<-table.element(a,'Fit',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Random',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:length(m$trend)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
+ a<-table.element(a,signif(m$trend[i],6))
+ a<-table.element(a,signif(m$seasonal[i],6))
+ a<-table.element(a,signif(m$random[i],6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/58mlh1386251467.tab") 
> 
> try(system("convert tmp/1xlwt1386251467.ps tmp/1xlwt1386251467.png",intern=TRUE))
character(0)
> try(system("convert tmp/25pd41386251467.ps tmp/25pd41386251467.png",intern=TRUE))
character(0)
> try(system("convert tmp/32amk1386251467.ps tmp/32amk1386251467.png",intern=TRUE))
character(0)
> try(system("convert tmp/449ze1386251467.ps tmp/449ze1386251467.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.781   0.942   4.705