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(19.785,18.479,10.698,31.956,29.506,34.506,27.165,26.736,23.691,18.157,17.328,18.205,20.995,17.382,9.367,31.124,26.551,30.651,25.859,25.100,25.778,20.418,18.688,20.424,24.776,19.814,12.738,31.566,30.111,30.019,31.934,25.826,26.835,20.205,17.789,20.520,22.518,15.572,11.509,25.447,24.090,27.786,26.195,20.516,22.759,19.028,16.971,20.036,22.485,18.730,14.538,27.561,25.985,34.670,32.066,27.186,29.586,21.359,21.553,19.573,24.256,22.380,16.167,27.297,28.287,33.474,28.229,28.785,25.597,18.130,20.198,22.849,23.118)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> 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  -0.8800026 23.47841 -2.813405772
Feb 1  -4.6005301 23.42082 -0.341289493
Mar 1 -10.8207905 23.36323 -1.844440397
Apr 1   5.8254420 23.28541  2.845151956
May 1   4.0791737 23.20758  2.219245017
Jun 1   8.4829486 23.13572  2.887329276
Jul 1   5.1810609 23.06386 -1.079923873
Aug 1   2.2649832 22.99331  1.477706942
Sep 1   2.2482440 22.92276 -1.480000667
Oct 1  -3.9072658 22.73643 -0.672166807
Nov 1  -4.6996108 22.55011 -0.522497812
Dec 1  -3.1736521 22.38725 -1.008594871
Jan 2  -0.8800026 22.22439 -0.349382735
Feb 2  -4.6005301 22.20831 -0.225781840
Mar 2 -10.8207905 22.19224 -2.004448128
Apr 2   5.8254420 22.31115  2.987406395
May 2   4.0791737 22.43006  0.041761627
Jun 2   8.4829486 22.63511 -0.467057598
Jul 2   5.1810609 22.84015 -2.162214231
Aug 2   2.2649832 23.05702 -0.222001635
Sep 2   2.2482440 23.27388  0.255872535
Oct 2  -3.9072658 23.48590  0.839364829
Nov 2  -4.6996108 23.69792 -0.310307743
Dec 2  -3.1736521 23.89959 -0.301937886
Jan 3  -0.8800026 24.10126  1.554741166
Feb 3  -4.6005301 24.24412  0.170410980
Mar 3 -10.8207905 24.38698 -0.828186389
Apr 3   5.8254420 24.39982  1.340733712
May 3   4.0791737 24.41267  1.619154521
Jun 3   8.4829486 24.31715 -2.781101592
Jul 3   5.1810609 24.22163  2.531304887
Aug 3   2.2649832 23.99086 -0.429846143
Sep 3   2.2482440 23.76009  0.826664403
Oct 3  -3.9072658 23.40907  0.703198774
Nov 3  -4.6996108 23.05804 -0.569431722
Dec 3  -3.1736521 22.64331  1.050339368
Jan 4  -0.8800026 22.22858  1.169419652
Feb 4  -4.6005301 21.83750 -1.664970520
Mar 4 -10.8207905 21.44642  0.883372125
Apr 4   5.8254420 21.21531 -1.593754384
May 4   4.0791737 20.98421 -0.973380184
Jun 4   8.4829486 20.96895 -1.665894382
Jul 4   5.1810609 20.95369  0.060254011
Aug 4   2.2649832 21.14305 -2.892037776
Sep 4   2.2482440 21.33242 -0.821667988
Oct 4  -3.9072658 21.63375  1.301520003
Nov 4  -4.6996108 21.93507 -0.264456873
Dec 4  -3.1736521 22.34930  0.860355307
Jan 5  -0.8800026 22.76353  0.601476683
Feb 5  -4.6005301 23.22075  0.109778468
Mar 5 -10.8207905 23.67798  1.680813071
Apr 5   5.8254420 24.03334 -2.297780987
May 5   4.0791737 24.38870 -2.482874337
Jun 5   8.4829486 24.60035  1.586703971
Jul 5   5.1810609 24.81199  2.072944871
Aug 5   2.2649832 24.98348 -0.062460225
Sep 5   2.2482440 25.15496  2.182796254
Oct 5  -3.9072658 25.22586  0.040408947
Nov 5  -4.6996108 25.29675  0.955856774
Dec 5  -3.1736521 25.21860 -2.471948341
Jan 6  -0.8800026 25.14045 -0.004444261
Feb 6  -4.6005301 24.97954  2.000992499
Mar 6 -10.8207905 24.81863  2.169162077
Apr 6   5.8254420 24.70399 -3.232429241
May 6   4.0791737 24.58935 -0.381519850
Jun 6   8.4829486 24.53014  0.460914291
Jul 6   5.1810609 24.47093 -1.422988975
Aug 6   2.2649832 24.41417  2.105849252
Sep 6   2.2482440 24.35741 -1.008650946
Oct 6  -3.9072658 24.30506 -2.267790434
Nov 6  -4.6996108 24.25271  0.644905213
Dec 6  -3.1736521 24.21103  1.811619271
Jan 7  -0.8800026 24.16936 -0.171357475
> m$win
  s   t   l 
731  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
74  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1nb741322579611.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/25gpk1322579611.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$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3m9jk1322579611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$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$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/431031322579611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$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/55jwu1322579611.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/6s89e1322579611.tab") 
> 
> try(system("convert tmp/1nb741322579611.ps tmp/1nb741322579611.png",intern=TRUE))
character(0)
> try(system("convert tmp/25gpk1322579611.ps tmp/25gpk1322579611.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m9jk1322579611.ps tmp/3m9jk1322579611.png",intern=TRUE))
character(0)
> try(system("convert tmp/431031322579611.ps tmp/431031322579611.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.363   0.303   1.688