R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(274,291,280,258,252,251,224,225,234,233,229,208,224,226,223,205,201,202,183,188,200,206,211,201,299,244,251,241,244,252,234,246,265,277,287,275,320,338,342,322,323,343,315,334,359,362,378,345,422,430,443,431,425,432,387,396,411,421,424,410,464,486,490,459,454,446,406,412,428,429,425,396,429,439,424,379,370,353,322,322,338,348,350,312,358,378,352,312,310,292,276,269,286,292,288,255,304,299,293,275,272,264,234,231,263,264,264,245,297,317,318,315,312,310,306,313,350,354,371,357,419,425,424,399,393,378,371,364,384,377,383,352)
> par2 = '12'
> par1 = 'multiplicative'
> par2 <- as.numeric(par2)
> x <- ts(x,freq=par2)
> m <- decompose(x,type=par1)
> m$figure
 [1] 1.0951698 1.0963069 1.0852301 1.0137380 1.0000592 0.9876653 0.9067977
 [8] 0.9182575 0.9786573 0.9916348 1.0001513 0.9263321
> postscript(file="/var/wessaorg/rcomp/tmp/1pvl01322753049.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m)
> dev.off()
null device 
          1 
> mylagmax <- length(x)/2
> postscript(file="/var/wessaorg/rcomp/tmp/2j6ya1322753049.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3g7uu1322753049.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/4pcey1322753049.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$trend)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$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/5gp8y1322753049.tab") 
> 
> try(system("convert tmp/1pvl01322753049.ps tmp/1pvl01322753049.png",intern=TRUE))
character(0)
> try(system("convert tmp/2j6ya1322753049.ps tmp/2j6ya1322753049.png",intern=TRUE))
character(0)
> try(system("convert tmp/3g7uu1322753049.ps tmp/3g7uu1322753049.png",intern=TRUE))
character(0)
> try(system("convert tmp/4pcey1322753049.ps tmp/4pcey1322753049.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.625   0.200   1.833