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(111.4,87.4,96.8,114.1,110.3,103.9,101.6,94.6,95.9,104.7,102.8,98.1,113.9,80.9,95.7,113.2,105.9,108.8,102.3,99,100.7,115.5,100.7,109.9,114.6,85.4,100.5,114.8,116.5,112.9,102,106,105.3,118.8,106.1,109.3,117.2,92.5,104.2,112.5,122.4,113.3,100,110.7,112.8,109.8,117.3,109.1,115.9,96,99.8,116.8,115.7,99.4,94.3,91,93.2,103.1,94.1,91.8,102.7)
> 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   9.16838098 103.66827 -1.43665395
Feb 1 -17.17193236 103.36826  1.20367368
Mar 1  -6.06557350 103.06824 -0.20267087
Apr 1   8.95722356 102.78526  2.35751755
May 1   8.98002436 102.50227 -1.18229776
Jun 1   2.60386790 102.24294 -0.94680526
Jul 1  -4.89229589 101.98360  4.50869456
Aug 1  -4.50979903 101.73644 -2.62663880
Sep 1  -3.02730723 101.48927 -2.56196712
Oct 1   6.01711529 101.29348 -2.61059779
Nov 1   0.08153629 101.09769  1.62077307
Dec 1  -0.14124097 101.19654 -2.95530244
Jan 2   9.16838098 101.29540  3.43622285
Feb 2 -17.17193236 101.64576 -3.57382535
Mar 2  -6.06557350 101.99612 -0.23054576
Apr 2   8.95722356 102.47584  1.76693979
May 2   8.98002436 102.95555 -6.03557840
Jun 2   2.60386790 103.40158  2.79454776
Jul 2  -4.89229589 103.84761  3.34468124
Aug 2  -4.50979903 104.23737 -0.72756965
Sep 2  -3.02730723 104.62712 -0.89981549
Oct 2   6.01711529 104.98178  4.50110445
Nov 2   0.08153629 105.33644 -4.71797408
Dec 2  -0.14124097 105.67088  4.37035885
Jan 3   9.16838098 106.00533 -0.57370743
Feb 3 -17.17193236 106.34770 -3.77576719
Mar 3  -6.06557350 106.69007 -0.12449915
Apr 3   8.95722356 107.04895 -1.20617582
May 3   8.98002436 107.40783  0.11214377
Jun 3   2.60386790 107.73018  2.56595003
Jul 3  -4.89229589 108.05253 -1.16023640
Aug 3  -4.50979903 108.32486  2.18493622
Sep 3  -3.02730723 108.59719 -0.26988611
Oct 3   6.01711529 108.76091  4.02197827
Nov 3   0.08153629 108.92462 -2.90615582
Dec 3  -0.14124097 108.99794  0.44329625
Jan 4   9.16838098 109.07127 -1.03965088
Feb 4 -17.17193236 109.21833  0.45360293
Mar 4  -6.06557350 109.36539  0.90018454
Apr 4   8.95722356 109.57375 -6.03097510
May 4   8.98002436 109.78211  3.63786152
Jun 4   2.60386790 109.97816  0.71797307
Jul 4  -4.89229589 110.17420 -5.28190807
Aug 4  -4.50979903 110.24079  4.96901182
Sep 4  -3.02730723 110.30737  5.51993675
Oct 4   6.01711529 110.11705 -6.33416746
Nov 4   0.08153629 109.92673  7.29172985
Dec 4  -0.14124097 109.20294  0.03830055
Jan 5   9.16838098 108.47915 -1.74752797
Feb 5 -17.17193236 107.27611  5.89581747
Mar 5  -6.06557350 106.07308 -0.20750929
Apr 5   8.95722356 104.60562  3.23715316
May 5   8.98002436 103.13816  3.58181188
Jun 5   2.60386790 101.65643 -4.86029803
Jul 5  -4.89229589 100.17470 -0.98240062
Aug 5  -4.50979903  98.66371 -3.15390685
Sep 5  -3.02730723  97.15272 -0.92540803
Oct 5   6.01711529  95.63205  1.45083033
Nov 5   0.08153629  94.11139 -0.09292979
Dec 5  -0.14124097  92.60472 -0.66348066
Jan 6   9.16838098  91.09805  2.43356925
> m$win
  s   t   l 
611  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
62  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/140ek1259702273.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/242ru1259702273.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3ta6t1259702273.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/4v6sr1259702273.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/51l3d1259702273.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/60juv1259702273.tab") 
> system("convert tmp/140ek1259702273.ps tmp/140ek1259702273.png")
> system("convert tmp/242ru1259702273.ps tmp/242ru1259702273.png")
> system("convert tmp/3ta6t1259702273.ps tmp/3ta6t1259702273.png")
> system("convert tmp/4v6sr1259702273.ps tmp/4v6sr1259702273.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.968   0.635   1.148