R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(105.7,105.7,111.1,82.4,60,107.3,99.3,113.5,108.9,100.2,103.9,138.7,120.2,100.2,143.2,70.9,85.2,133,136.6,117.9,106.3,122.3,125.5,148.4,126.3,99.6,140.4,80.3,92.6,138.5,110.9,119.6,105,109,129.4,148.6,101.4,134.8,143.7,81.6,90.3,141.5,140.7,140.2,100.2,125.7,119.6,134.7,109,116.3,146.9,97.4,89.4,132.1,139.8,129,112.5,121.9,121.7,123.1)
> 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  -1.6547509  99.61625   7.73850266
Feb 1  -3.3354675 100.19607   8.83939638
Mar 1  21.9238311 100.77589 -11.59972507
Apr 1 -32.8580649 101.47495  13.78311243
May 1 -32.1199340 102.17401 -10.05407707
Jun 1  14.7768551 102.91158 -10.38843451
Jul 1   9.6736359 103.64915 -14.02278377
Aug 1   8.1417591 104.37500   0.98324272
Sep 1  -9.4301217 105.10085  13.22927312
Oct 1  -0.4502835 106.36754  -5.71725265
Nov 1   3.4895525 107.63422  -7.22377617
Dec 1  21.8429880 109.28371   7.57330189
Jan 2  -1.6547509 110.93320  10.92155438
Feb 2  -3.3354675 112.22538  -8.68991193
Mar 2  21.9238311 113.51756   7.75860659
Apr 2 -32.8580649 114.52866 -10.77059609
May 2 -32.1199340 115.53976   1.78017423
Jun 2  14.7768551 116.46921   1.75393306
Jul 2   9.6736359 117.39866   9.52770007
Aug 2   8.1417591 117.87702  -8.11877657
Sep 2  -9.4301217 118.35537  -2.62524930
Oct 2  -0.4502835 118.60403   4.14625369
Nov 2   3.4895525 118.85269   3.15775892
Dec 2  21.8429880 118.70928   7.84773332
Jan 3  -1.6547509 118.56587   9.38888214
Feb 3  -3.3354675 118.03060 -15.09513629
Mar 3  21.9238311 117.49534   0.98083010
Apr 3 -32.8580649 116.93600  -3.77793663
May 3 -32.1199340 116.37666   8.34326963
Jun 3  14.7768551 116.18038   7.54276265
Jul 3   9.6736359 115.98410 -14.75773615
Aug 3   8.1417591 116.38281  -4.92456977
Sep 3  -9.4301217 116.78152  -2.35139946
Oct 3  -0.4502835 117.32029  -7.87000202
Nov 3   3.4895525 117.85905   8.05139766
Dec 3  21.8429880 118.78458   7.97243503
Jan 4  -1.6547509 119.71010 -16.65535318
Feb 4  -3.3354675 120.79168  17.34378692
Mar 4  21.9238311 121.87326  -0.09708815
Apr 4 -32.8580649 122.24414  -7.78607026
May 4 -32.1199340 122.61501  -0.19507937
Jun 4  14.7768551 122.23432   4.48882743
Jul 4   9.6736359 121.85362   9.17274242
Aug 4   8.1417591 121.49515  10.56308818
Sep 4  -9.4301217 121.13668 -11.50656215
Oct 4  -0.4502835 120.98902   5.16125898
Nov 4   3.4895525 120.84137  -4.73091765
Dec 4  21.8429880 120.71404  -7.85702997
Jan 5  -1.6547509 120.58672  -9.93196786
Feb 5  -3.3354675 120.61270  -0.97723228
Mar 5  21.9238311 120.63868   4.33748812
Apr 5 -32.8580649 120.52452   9.73354144
May 5 -32.1199340 120.41037   1.10956776
Jun 5  14.7768551 120.01122  -2.68807815
Jul 5   9.6736359 119.61208  10.51428412
Aug 5   8.1417591 119.15852   1.69972016
Sep 5  -9.4301217 118.70496   3.22516012
Oct 5  -0.4502835 118.16084   4.18944553
Nov 5   3.4895525 117.61671   0.59373318
Dec 5  21.8429880 116.96483 -15.70781958
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/13dld1259698441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2p1l91259698441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/www/html/rcomp/tmp/3njpe1259698441.ps",horizontal=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/www/html/rcomp/tmp/4640e1259698441.ps",horizontal=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/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/580fc1259698441.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/www/html/rcomp/tmp/6h8j71259698441.tab") 
> system("convert tmp/13dld1259698441.ps tmp/13dld1259698441.png")
> system("convert tmp/2p1l91259698441.ps tmp/2p1l91259698441.png")
> system("convert tmp/3njpe1259698441.ps tmp/3njpe1259698441.png")
> system("convert tmp/4640e1259698441.ps tmp/4640e1259698441.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.936   0.598   1.144