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(9.911,8.915,9.452,9.112,8.472,8.230,8.384,8.625,8.221,8.649,8.625,10.443,10.357,8.586,8.892,8.329,8.101,7.922,8.120,7.838,7.735,8.406,8.209,9.451,10.041,9.411,10.405,8.467,8.464,8.102,7.627,7.513,7.510,8.291,8.064,9.383,9.706,8.579,9.474,8.318,8.213,8.059,9.111,7.708,7.680,8.014,8.007,8.718,9.486,9.113,9.025,8.476,7.952,7.759,7.835,7.600,7.651,8.319,8.812,8.630)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1) #seasonal period
> if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
> par3 <- as.numeric(par3) #s.degree
> if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
> par5 <- as.numeric(par5)#t.degree
> if (par6 != '') par6 <- as.numeric(par6)#l.window
> par7 <- as.numeric(par7)#l.degree
> if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
> nx <- length(x)
> x <- ts(x,frequency=par1)
> if (par6 != '') {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
+ } else {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
+ }
> m$time.series
         seasonal    trend     remainder
Jan 1  1.30108166 8.730648 -0.1207292759
Feb 1  0.32594771 8.758336 -0.1692840380
Mar 1  0.85901425 8.786025 -0.1930392852
Apr 1 -0.04563989 8.808325  0.3493152315
May 1 -0.34109326 8.830624 -0.0175310107
Jun 1 -0.55906374 8.847235 -0.0581714040
Jul 1 -0.35003422 8.863846 -0.1298118008
Aug 1 -0.70830090 8.874692  0.4586089093
Sep 1 -0.80536725 8.885538  0.1408292935
Oct 1 -0.22768575 8.863954  0.0127318986
Nov 1 -0.21880451 8.842370  0.0014347613
Dec 1  0.76994558 8.793098  0.8799564451
Jan 2  1.30108166 8.743826  0.3120921382
Feb 2  0.32594771 8.694198 -0.4341453296
Mar 2  0.85901425 8.644569 -0.6115832824
Apr 2 -0.04563989 8.598121 -0.2234815496
May 2 -0.34109326 8.551674 -0.1095805756
Jun 2 -0.55906374 8.531595 -0.0505309407
Jul 2 -0.35003422 8.511516 -0.0414813093
Aug 2 -0.70830090 8.546847 -0.0005463287
Sep 2 -0.80536725 8.582179 -0.0418116741
Oct 2 -0.22768575 8.632745  0.0009405546
Nov 2 -0.21880451 8.683311 -0.2555069591
Dec 2  0.76994558 8.697876 -0.0168214338
Jan 3  1.30108166 8.712440  0.0274781010
Feb 3  0.32594771 8.697081  0.3879717291
Mar 3  0.85901425 8.681721  0.8642648722
Apr 3 -0.04563989 8.655554 -0.1429140093
May 3 -0.34109326 8.629387  0.1757063503
Jun 3 -0.55906374 8.592172  0.0688913624
Jul 3 -0.35003422 8.554958 -0.5779236290
Aug 3 -0.70830090 8.507806 -0.2865049151
Sep 3 -0.80536725 8.460654 -0.1452865272
Oct 3 -0.22768575 8.435962  0.0827240736
Nov 3 -0.21880451 8.411270 -0.1284650679
Dec 3  0.76994558 8.433981  0.1790731500
Jan 4  1.30108166 8.456693 -0.0517746226
Feb 4  0.32594771 8.490706 -0.2376536326
Mar 4  0.85901425 8.524719  0.0902668724
Apr 4 -0.04563989 8.529264 -0.1656245263
May 4 -0.34109326 8.533810  0.0202833161
Jun 4 -0.55906374 8.517275  0.1007888828
Jul 4 -0.35003422 8.500740  0.9602944459
Aug 4 -0.70830090 8.485567 -0.0692659675
Sep 4 -0.80536725 8.470394  0.0149732931
Oct 4 -0.22768575 8.448284 -0.2065981665
Nov 4 -0.21880451 8.426174 -0.2003693686
Dec 4  0.76994558 8.391871 -0.4438169133
Jan 5  1.30108166 8.357569 -0.1726504487
Feb 5  0.32594771 8.338695  0.4483568256
Mar 5  0.85901425 8.319822 -0.1538363851
Apr 5 -0.04563989 8.338453  0.1831867926
May 5 -0.34109326 8.357084 -0.0639907885
Jun 5 -0.55906374 8.368500 -0.0504358031
Jul 5 -0.35003422 8.379915 -0.1948808212
Aug 5 -0.70830090 8.389626 -0.0813251146
Sep 5 -0.80536725 8.399337  0.0570302660
Oct 5 -0.22768575 8.409670  0.1370155584
Nov 5 -0.21880451 8.420003  0.6108011085
Dec 5  0.76994558 8.430945 -0.5708909342
> 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$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1wc1c1322570219.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2ubf31322570219.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3szc21322570219.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/4rwy41322570219.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5rlhi1322570219.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/66sja1322570219.tab") 
> 
> try(system("convert tmp/1wc1c1322570219.ps tmp/1wc1c1322570219.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ubf31322570219.ps tmp/2ubf31322570219.png",intern=TRUE))
character(0)
> try(system("convert tmp/3szc21322570219.ps tmp/3szc21322570219.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rwy41322570219.ps tmp/4rwy41322570219.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.463   0.224   1.749