R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(20995,17382,9367,31124,26551,30651,25859,25100,25778,20418,18688,20424,24776,19814,12738,31566,30111,30019,31934,25826,26835,20205,17789,20520,22518,15572,11509,25447,24090,27786,26195,20516,22759,19028,16971,20036,22485,18730,14538,27561,25985,34670,32066,27186,29586,21359,21553,19573,24256,22380,16167,27297,28287,33474,28229,28785,25597,18130,20198,22849,23118)
> 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   -295.1638 21633.47  -343.30570
Feb 1  -4491.9076 21834.85    39.06204
Mar 1 -10466.5723 22036.22 -2202.64937
Apr 1   5221.3996 22240.84  3661.76527
May 1   3579.9725 22445.45   525.57898
Jun 1   7856.9420 22658.85   135.20830
Jul 1   5355.3138 22872.25 -2368.56472
Aug 1   1946.9117 23081.50    71.58650
Sep 1   2540.9140 23290.75   -53.66661
Oct 1  -3756.4042 23476.19   698.21503
Nov 1  -4558.9237 23661.63  -414.70205
Dec 1  -2932.4822 23867.55  -511.06579
Jan 2   -295.1638 24073.47   997.69355
Feb 2  -4491.9076 24233.51    72.39372
Mar 2 -10466.5723 24393.56 -1188.98525
Apr 2   5221.3996 24419.03  1925.57066
May 2   3579.9725 24444.50  2086.52565
Jun 2   7856.9420 24348.59 -2186.52753
Jul 2   5355.3138 24252.67  2326.01696
Aug 2   1946.9117 24004.17  -125.08345
Sep 2   2540.9140 23755.67   538.41181
Oct 2  -3756.4042 23388.71   572.69222
Nov 2  -4558.9237 23021.75  -673.82608
Dec 2  -2932.4822 22611.27   841.21141
Jan 3   -295.1638 22200.79   612.37199
Feb 3  -4491.9076 21826.90 -1762.98780
Mar 3 -10466.5723 21453.00   522.57326
Apr 3   5221.3996 21234.52 -1008.91741
May 3   3579.9725 21016.04  -506.00902
Jun 3   7856.9420 21000.38 -1071.32028
Jul 3   5355.3138 20984.72  -145.03387
Aug 3   1946.9117 21156.36 -2587.27506
Sep 3   2540.9140 21328.01 -1109.92058
Oct 3  -3756.4042 21613.39  1171.01343
Nov 3  -4558.9237 21898.77  -368.85127
Dec 3  -2932.4822 22317.25   651.22731
Jan 4   -295.1638 22735.73    44.42898
Feb 4  -4491.9076 23210.15    11.76117
Mar 4 -10466.5723 23684.56  1320.01421
Apr 4   5221.3996 24052.54 -1712.94400
May 4   3579.9725 24420.53 -2015.50313
Jun 4   7856.9420 24631.78  2181.27812
Jul 4   5355.3138 24843.03  1867.65703
Aug 4   1946.9117 24996.79   242.30251
Sep 4   2540.9140 25150.54  1894.54367
Oct 4  -3756.4042 25205.50   -90.09764
Nov 4  -4558.9237 25260.46   851.46233
Dec 4  -2932.4822 25186.56 -2681.07638
Jan 5   -295.1638 25112.66  -561.49200
Feb 5  -4491.9076 24968.93  1902.97517
Mar 5 -10466.5723 24825.21  1808.36321
Apr 5   5221.3996 24710.76 -2635.16094
May 5   3579.9725 24596.31   110.71399
Jun 5   7856.9420 24517.10  1099.95319
Jul 5   5355.3138 24437.90 -1564.20995
Aug 5   1946.9117 24357.43  2480.65709
Sep 5   2540.9140 24276.97 -1220.88021
Oct 5  -3756.4042 24193.41 -2307.00259
Nov 5  -4558.9237 24109.85   647.07631
Dec 5  -2932.4822 24028.59  1752.88796
Jan 6   -295.1638 23947.34  -534.17730
> 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$outer
[1] 0
> postscript(file="/var/www/rcomp/tmp/1f31u1322499506.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/rcomp/tmp/2kohb1322499506.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/www/rcomp/tmp/36npz1322499506.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/www/rcomp/tmp/44a221322499506.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/5ja9w1322499506.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/rcomp/tmp/695ac1322499506.tab") 
> 
> try(system("convert tmp/1f31u1322499506.ps tmp/1f31u1322499506.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kohb1322499506.ps tmp/2kohb1322499506.png",intern=TRUE))
character(0)
> try(system("convert tmp/36npz1322499506.ps tmp/36npz1322499506.png",intern=TRUE))
character(0)
> try(system("convert tmp/44a221322499506.ps tmp/44a221322499506.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.680   0.272   2.038