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(6.02,5.62,4.87,4.24,4.02,3.74,3.45,3.34,3.21,3.12,3.04,2.97,2.93,2.95,2.92,2.9,2.95,2.91,2.89,2.84,2.82,2.78,2.86,2.87,2.94,3.04,3.12,3.19,3.27,3.34,3.4,3.55,3.64,3.76,3.78,3.77,3.81,3.81,3.82,3.96,3.86,3.84,3.68,3.56,3.48,3.4,3.42,3.2,3.11,3.1,2.99,3.1,3,3.05,3.1,3.2,3.1,3.3,3.13,3.14)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> par8 <- 'FALSE'
> par7 <- '1'
> par6 <- ''
> par5 <- '1'
> par4 <- ''
> par3 <- '0'
> par2 <- 'periodic'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Decomposition by Loess (v1.0.2) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_decomposeloess.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1) #seasonal period
> if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
> par3 <- as.numeric(par3) #s.degree
> if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
> par5 <- as.numeric(par5)#t.degree
> if (par6 != '') par6 <- as.numeric(par6)#l.window
> par7 <- as.numeric(par7)#l.degree
> if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
> nx <- length(x)
> x <- ts(x,frequency=par1)
> if (par6 != '') {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
+ } else {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
+ }
> m$time.series
          seasonal    trend    remainder
Jan 1  0.158600416 5.270678  0.590721633
Feb 1  0.150240714 5.031249  0.438510253
Mar 1  0.039881120 4.791820  0.038298766
Apr 1  0.005569801 4.563355 -0.328925075
May 1 -0.020741590 4.334890 -0.294148844
Jun 1 -0.035815196 4.113623 -0.337807452
Jul 1 -0.078888818 3.892355 -0.363466045
Aug 1 -0.052132596 3.677031 -0.284898765
Sep 1 -0.067376323 3.461708 -0.184331536
Oct 1 -0.018538615 3.313139 -0.174600730
Nov 1 -0.017700810 3.164571 -0.106870021
Dec 1 -0.063097767 3.094378 -0.061279831
Jan 2  0.158600416 3.024184 -0.252784782
Feb 2  0.150240714 2.985272 -0.185512547
Mar 2  0.039881120 2.946359 -0.066240419
Apr 2  0.005569801 2.926388 -0.031957665
May 2 -0.020741590 2.906416  0.064325161
Jun 2 -0.035815196 2.900238  0.045577176
Jul 2 -0.078888818 2.894060  0.074829207
Aug 2 -0.052132596 2.898893 -0.006760441
Sep 2 -0.067376323 2.903726 -0.016350139
Oct 2 -0.018538615 2.920525 -0.121985936
Nov 2 -0.017700810 2.937323 -0.059621829
Dec 2 -0.063097767 2.973070 -0.039972587
Jan 3  0.158600416 3.008818 -0.227418487
Feb 3  0.150240714 3.068032 -0.178272457
Mar 3  0.039881120 3.127245 -0.047126534
Apr 3  0.005569801 3.205144 -0.020713325
May 3 -0.020741590 3.283042  0.007699955
Jun 3 -0.035815196 3.362934  0.012881106
Jul 3 -0.078888818 3.442827  0.036062273
Aug 3 -0.052132596 3.511132  0.091000234
Sep 3 -0.067376323 3.579438  0.127938144
Oct 3 -0.018538615 3.632695  0.145843140
Nov 3 -0.017700810 3.685953  0.111748040
Dec 3 -0.063097767 3.720238  0.112860230
Jan 4  0.158600416 3.754522 -0.103122721
Feb 4  0.150240714 3.760435 -0.100675379
Mar 4  0.039881120 3.766347  0.013771857
Apr 4  0.005569801 3.745755  0.208674997
May 4 -0.020741590 3.725163  0.155578209
Jun 4 -0.035815196 3.681532  0.194282840
Jul 4 -0.078888818 3.637901  0.120987486
Aug 4 -0.052132596 3.572364  0.039768512
Sep 4 -0.067376323 3.506827  0.040549488
Oct 4 -0.018538615 3.430310 -0.011771689
Nov 4 -0.017700810 3.353794  0.083907038
Dec 4 -0.063097767 3.289559 -0.026461429
Jan 5  0.158600416 3.225325 -0.273925036
Feb 5  0.150240714 3.186565 -0.236805666
Mar 5  0.039881120 3.147805 -0.197686403
Apr 5  0.005569801 3.148071 -0.053640647
May 5 -0.020741590 3.148336 -0.127594820
Jun 5 -0.035815196 3.150251 -0.064436108
Jul 5 -0.078888818 3.152166  0.026722619
Aug 5 -0.052132596 3.158076  0.094056562
Sep 5 -0.067376323 3.163986  0.003390455
Oct 5 -0.018538615 3.173584  0.144954843
Nov 5 -0.017700810 3.183182 -0.035480865
Dec 5 -0.063097767 3.194765  0.008332397
> m$win
  s   t   l 
601  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
61  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1rws61384347123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2epfw1384347123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
> acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
> acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3fw8f1384347123.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$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4k33s1384347123.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$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
> 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,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Component',header=TRUE)
> a<-table.element(a,'Window',header=TRUE)
> a<-table.element(a,'Degree',header=TRUE)
> a<-table.element(a,'Jump',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,m$win['s'])
> a<-table.element(a,m$deg['s'])
> a<-table.element(a,m$jump['s'])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,m$win['t'])
> a<-table.element(a,m$deg['t'])
> a<-table.element(a,m$jump['t'])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Low-pass',header=TRUE)
> a<-table.element(a,m$win['l'])
> a<-table.element(a,m$deg['l'])
> a<-table.element(a,m$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/532sq1384347123.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$time.series[i,'remainder'])
+ a<-table.element(a,m$time.series[i,'seasonal'])
+ a<-table.element(a,m$time.series[i,'trend'])
+ a<-table.element(a,m$time.series[i,'remainder'])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/60hip1384347123.tab") 
> 
> try(system("convert tmp/1rws61384347123.ps tmp/1rws61384347123.png",intern=TRUE))
character(0)
> try(system("convert tmp/2epfw1384347123.ps tmp/2epfw1384347123.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fw8f1384347123.ps tmp/3fw8f1384347123.png",intern=TRUE))
character(0)
> try(system("convert tmp/4k33s1384347123.ps tmp/4k33s1384347123.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.391   0.454   2.825