R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-redhat-linux-gnu (64-bit)

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> x <- c(349
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> par2 = '12'
> par1 = 'additive'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par2 <- as.numeric(par2)
> x <- ts(x,freq=par2)
> m <- decompose(x,type=par1)
> m$figure
 [1]   9.713281   4.855990   2.442448  -2.623177 -13.102344 -13.513802
 [7]   6.614323  12.974740   3.184115  -1.041927  -5.324219  -4.179427
> postscript(file="/var/www/wessaorg/rcomp/tmp/13ase1296472287.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/www/wessaorg/rcomp/tmp/247us1296472287.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$random),na.action=na.pass,lag.max = mylagmax,main='Random')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/wessaorg/rcomp/tmp/3hm0v1296472287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$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$random)]),main='Random')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/wessaorg/rcomp/tmp/4fdl11296472287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$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$random)]),main='Random')
> par(op)
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observations',header=TRUE)
> a<-table.element(a,'Fit',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Random',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:length(m$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/www/wessaorg/rcomp/tmp/5ab7d1296472287.tab") 
> 
> try(system("convert tmp/13ase1296472287.ps tmp/13ase1296472287.png",intern=TRUE))
character(0)
> try(system("convert tmp/247us1296472287.ps tmp/247us1296472287.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hm0v1296472287.ps tmp/3hm0v1296472287.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fdl11296472287.ps tmp/4fdl11296472287.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
 10.530   0.190  10.891