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(20366,22782,19169,13807,29743,25591,29096,26482,22405,27044,17970,18730,19684,19785,18479,10698,31956,29506,34506,27165,26736,23691,18157,17328,18205,20995,17382,9367,31124,26551,30651,25859,25100,25778,20418,18688,20424,24776,19814,12738,31566,30111,30019,31934,25826,26835,20205,17789,20520,22518,15572,11509,25447,24090,27786,26195,20516,22759,19028,16971,20036)
> 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  -2808.362 23476.65  -302.285614
Feb 1   -757.585 23331.07   208.515541
Mar 1  -4792.049 23185.49   775.557643
Apr 1 -11227.753 23058.68  1976.071732
May 1   7139.347 22931.87  -328.218645
Jun 1   4347.983 22818.32 -1575.304940
Jul 1   7595.819 22704.77 -1204.591326
Aug 1   4745.290 22581.99  -845.276534
Sep 1   1368.964 22459.20 -1423.163989
Oct 1   2536.226 22409.72  2098.051717
Nov 1  -3467.109 22360.24  -923.134712
Dec 1  -4680.770 22561.71   849.061213
Jan 2  -2808.362 22763.17  -270.811114
Feb 2   -757.585 22988.48 -2445.893978
Mar 2  -4792.049 23213.78    57.264107
Apr 2 -11227.753 23288.00 -1362.250059
May 2   7139.347 23362.22  1454.431309
Jun 2   4347.983 23328.28  1829.739323
Jul 2   7595.819 23294.33  3615.847245
Aug 2   4745.290 23199.64  -779.930262
Sep 2   1368.964 23104.95  2262.089983
Oct 2   2536.226 22929.71 -1774.932141
Nov 2  -3467.109 22754.47 -1130.356402
Dec 2  -4680.770 22546.38  -537.611745
Jan 3  -2808.362 22338.30 -1324.935340
Feb 3   -757.585 22237.13  -484.545955
Mar 3  -4792.049 22135.96    38.084378
Apr 3 -11227.753 22210.35 -1615.597585
May 3   7139.347 22284.74  1699.915988
Jun 3   4347.983 22463.77  -260.748166
Jul 3   7595.819 22642.79   412.387589
Aug 3   4745.290 22861.37 -1747.660259
Sep 3   1368.964 23079.95   651.089646
Oct 3   2536.226 23290.41   -48.638112
Nov 3  -3467.109 23500.88   384.231993
Dec 3  -4680.770 23688.93  -320.164415
Jan 4  -2808.362 23876.99  -644.629076
Feb 4   -757.585 24059.77  1473.816805
Mar 4  -4792.049 24242.55   363.503634
Apr 4 -11227.753 24336.46  -370.706367
May 4   7139.347 24430.37    -3.720834
Jun 4   4347.983 24400.36  1362.660943
Jul 4   7595.819 24370.34 -1947.157371
Aug 4   4745.290 24208.78  2979.929218
Sep 4   1368.964 24047.22   409.813560
Oct 4   2536.226 23745.61   553.162808
Nov 4  -3467.109 23444.00   228.109920
Dec 4  -4680.770 23035.20  -565.426576
Jan 5  -2808.362 22626.39   701.968675
Feb 5   -757.585 22205.99  1069.594289
Mar 5  -4792.049 21785.59 -1421.539148
Apr 5 -11227.753 21546.94  1189.813713
May 5   7139.347 21308.29 -3000.637892
Jun 5   4347.983 21245.79 -1503.771415
Jul 5   7595.819 21183.29  -993.105031
Aug 5   4745.290 21136.63   313.079219
Sep 5   1368.964 21089.98 -1942.938777
Oct 5   2536.226 21070.56  -847.783842
Nov 5  -3467.109 21051.14  1443.968958
Dec 5  -4680.770 21070.42   581.347015
Jan 6  -2808.362 21089.71  1754.656820
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1hcv81259929443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2i5xm1259929443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/30jd01259929443.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/4a2a51259929443.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5s21e1259929443.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/66qtj1259929443.tab") 
> system("convert tmp/1hcv81259929443.ps tmp/1hcv81259929443.png")
> system("convert tmp/2i5xm1259929443.ps tmp/2i5xm1259929443.png")
> system("convert tmp/30jd01259929443.ps tmp/30jd01259929443.png")
> system("convert tmp/4a2a51259929443.ps tmp/4a2a51259929443.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.938   0.612   1.152