R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1.2999,1.3074,1.3242,1.3516,1.3511,1.3419,1.3716,1.3622,1.3896,1.4227,1.4684,1.457,1.4718,1.4748,1.5527,1.5751,1.5557,1.5553,1.577,1.4975,1.437,1.3322,1.2732,1.3449,1.3239,1.2785,1.305,1.319,1.365,1.4016,1.4088,1.4268,1.4562,1.4816,1.4914,1.4614,1.4272,1.3686,1.3569,1.3406,1.2565,1.2209,1.277,1.2894,1.3067,1.3898,1.3661,1.322,1.336,1.3649,1.3999,1.4442,1.4349,1.4388,1.4264,1.4343,1.377,1.3706,1.3556,1.3179,1.2905,1.3224,1.3201,1.3162,1.2789,1.2526,1.2288,1.24,1.2856)
> par2 = '12'
> par1 = 'additive'
> par2 <- as.numeric(par2)
> x <- ts(x,freq=par2)
> m <- decompose(x,type=par1)
> m$figure
 [1] -0.0191193056 -0.0249509722  0.0020140278  0.0154959028  0.0005136111
 [6]  0.0042625694  0.0187923611  0.0086256944 -0.0002051389  0.0062040278
[11] -0.0013393056 -0.0102934722
> postscript(file="/var/wessaorg/rcomp/tmp/1asna1353787515.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m)
> dev.off()
null device 
          1 
> mylagmax <- length(x)/2
> postscript(file="/var/wessaorg/rcomp/tmp/2t9wd1353787515.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/wessaorg/rcomp/tmp/3bdy71353787515.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/wessaorg/rcomp/tmp/4upes1353787515.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/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,'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$trend)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,m$trend[i]+m$seasonal[i])
+ a<-table.element(a,m$trend[i])
+ a<-table.element(a,m$seasonal[i])
+ a<-table.element(a,m$random[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5pi4w1353787515.tab") 
> 
> try(system("convert tmp/1asna1353787515.ps tmp/1asna1353787515.png",intern=TRUE))
character(0)
> try(system("convert tmp/2t9wd1353787515.ps tmp/2t9wd1353787515.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bdy71353787515.ps tmp/3bdy71353787515.png",intern=TRUE))
character(0)
> try(system("convert tmp/4upes1353787515.ps tmp/4upes1353787515.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.174   0.496   3.637