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(1.3031,1.3241,1.2961,1.2865,1.2305,1.2101,1.2125,1.2350,1.2014,1.1992,1.1791,1.1832,1.2159,1.1922,1.2114,1.2614,1.2812,1.2786,1.2772,1.2815,1.2679,1.2765,1.3247,1.3191,1.3029,1.3234,1.3354,1.3651,1.3453,1.3534,1.3706,1.3638,1.4268,1.4485,1.4635,1.4587,1.4876,1.5189,1.5783,1.5633,1.5554,1.5757,1.5593,1.4660,1.4065,1.2759,1.2705,1.3954,1.2793,1.2694,1.3282,1.3230,1.4135,1.4042,1.4253,1.4322,1.4632,1.4713,1.5016,1.4318)
> 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 -0.018731086 1.295812  0.0260194305
Feb 1 -0.012941157 1.285391  0.0516502776
Mar 1  0.009288774 1.274970  0.0118411227
Apr 1  0.016243561 1.265506  0.0047507295
May 1  0.018538319 1.256041 -0.0440796348
Jun 1  0.015765304 1.247128 -0.0527929935
Jul 1  0.018352273 1.238214 -0.0440663359
Aug 1  0.003178343 1.229521  0.0023011189
Sep 1 -0.001255558 1.220827 -0.0181714550
Oct 1 -0.023880073 1.217527  0.0055530077
Nov 1 -0.014024569 1.214227 -0.0211025483
Dec 1 -0.010534103 1.217898 -0.0241642691
Jan 2 -0.018731086 1.221570  0.0130614589
Feb 2 -0.012941157 1.227209 -0.0220682346
Mar 2  0.009288774 1.232849 -0.0307379300
Apr 2  0.016243561 1.240809  0.0043475936
May 2  0.018538319 1.248769  0.0138931461
Jun 2  0.015765304 1.258824  0.0040104166
Jul 2  0.018352273 1.268880 -0.0100322968
Aug 2  0.003178343 1.278850 -0.0005284851
Sep 2 -0.001255558 1.288820 -0.0196647022
Oct 2 -0.023880073 1.297319  0.0030614241
Nov 2 -0.014024569 1.305817  0.0329075318
Dec 2 -0.010534103 1.312978  0.0166561243
Jan 3 -0.018731086 1.320139  0.0014921657
Feb 3 -0.012941157 1.328382  0.0079594615
Mar 3  0.009288774 1.336624 -0.0105132446
Apr 3  0.016243561 1.347548  0.0013083188
May 3  0.018538319 1.358472 -0.0317100889
Jun 3  0.015765304 1.372218 -0.0345831283
Jul 3  0.018352273 1.385964 -0.0337161515
Aug 3  0.003178343 1.403253 -0.0426315144
Sep 3 -0.001255558 1.420542  0.0075130941
Oct 3 -0.023880073 1.439625  0.0327547424
Nov 3 -0.014024569 1.458708  0.0188163721
Dec 3 -0.010534103 1.475711 -0.0064771520
Jan 4 -0.018731086 1.492714  0.0136167728
Feb 4 -0.012941157 1.499976  0.0318653315
Mar 4  0.009288774 1.507237  0.0617738883
Apr 4  0.016243561 1.500749  0.0463073403
May 4  0.018538319 1.494261  0.0426008211
Jun 4  0.015765304 1.478708  0.0812264029
Jul 4  0.018352273 1.463156  0.0777920008
Aug 4  0.003178343 1.442404  0.0204172381
Sep 4 -0.001255558 1.421653 -0.0138975533
Oct 4 -0.023880073 1.401444 -0.1016643482
Nov 4 -0.014024569 1.381236 -0.0967111617
Dec 4 -0.010534103 1.368532  0.0374020256
Jan 5 -0.018731086 1.355828 -0.0577973382
Feb 5 -0.012941157 1.355486 -0.0731451845
Mar 5  0.009288774 1.355144 -0.0362330328
Apr 5  0.016243561 1.369566 -0.0628095982
May 5  0.018538319 1.383988  0.0109738652
Jun 5  0.015765304 1.398180 -0.0097454618
Jul 5  0.018352273 1.412372 -0.0054247727
Aug 5  0.003178343 1.427417  0.0016042809
Sep 5 -0.001255558 1.442462  0.0219933057
Oct 5 -0.023880073 1.458414  0.0367658619
Nov 5 -0.014024569 1.474366  0.0412583993
Dec 5 -0.010534103 1.490796 -0.0484617503
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1wcxk1292181087.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2wcxk1292181087.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/html/rcomp/tmp/3olwn1292181087.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/html/rcomp/tmp/4zddq1292181087.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/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5owak1292181087.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/69e981292181087.tab") 
> 
> try(system("convert tmp/1wcxk1292181087.ps tmp/1wcxk1292181087.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wcxk1292181087.ps tmp/2wcxk1292181087.png",intern=TRUE))
character(0)
> try(system("convert tmp/3olwn1292181087.ps tmp/3olwn1292181087.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zddq1292181087.ps tmp/4zddq1292181087.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.957   0.618   2.282