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(3010,2910,3840,3580,3140,3550,3250,2820,2260,2060,2120,2210,2190,2180,2350,2440,2370,2440,2610,3040,3190,3120,3170,3600,3420,3650,4180,2960,2710,2950,3030,3770,4740,4450,5550,5580,5890,7480,10450,6360,6710,6200,4490,3480,2520,1920,2010,1950,2240,2370,2840,2700,2980,3290,3300,3000,2330,2190,1970,2170,2830,3190,3550,3240,3450,3570,3230,3260,2700)
> 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 -112.42986 3173.002   -50.572572
Feb 1  257.21978 3122.158  -469.377391
Mar 1 1165.20288 3071.313  -396.515669
Apr 1  181.67988 3012.307   386.013198
May 1  199.82477 2953.301   -13.125810
Jun 1  307.80795 2889.235   352.957183
Jul 1  -39.20886 2825.169   464.040164
Aug 1 -138.54966 2760.554   197.995161
Sep 1 -419.55688 2695.940   -16.383418
Oct 1 -653.16205 2606.554   106.607818
Nov 1 -440.55844 2517.168    43.390273
Dec 1 -308.26966 2437.669    80.600713
Jan 2 -112.42986 2358.170   -55.739876
Feb 2  257.21978 2355.618  -432.838054
Mar 2 1165.20288 2353.067 -1168.269691
Apr 2  181.67988 2432.928  -174.607762
May 2  199.82477 2512.789  -342.613708
Jun 2  307.80795 2645.271  -513.079312
Jul 2  -39.20886 2777.754  -128.544928
Aug 2 -138.54966 2916.198   262.352057
Sep 2 -419.55688 3054.641   554.915464
Oct 2 -653.16205 3140.439   632.722692
Nov 2 -440.55844 3226.237   384.321140
Dec 2 -308.26966 3250.303   657.966703
Jan 3 -112.42986 3274.369   258.061236
Feb 3  257.21978 3308.274    84.506307
Mar 3 1165.20288 3342.179  -327.382080
Apr 3  181.67988 3450.799  -672.479190
May 3  199.82477 3559.419 -1049.244175
Jun 3  307.80795 3771.120 -1128.928157
Jul 3  -39.20886 3982.821  -913.612152
Aug 3 -138.54966 4326.447  -417.897483
Sep 3 -419.55688 4670.073   489.483608
Oct 3 -653.16205 5057.066    46.096484
Nov 3 -440.55844 5444.058   546.500580
Dec 3 -308.26966 5701.668   186.602111
Jan 4 -112.42986 5959.277    43.152613
Feb 4  257.21978 5962.471  1260.309566
Mar 4 1165.20288 5965.664  3319.133061
Apr 4  181.67988 5738.935   439.385043
May 4  199.82477 5512.206   997.969149
Jun 4  307.80795 5135.373   756.819105
Jul 4  -39.20886 4758.540  -229.330951
Aug 4 -138.54966 4303.264  -684.714828
Sep 4 -419.55688 3847.989  -908.432281
Oct 4 -653.16205 3456.557  -883.395028
Nov 4 -440.55844 3065.125  -614.566555
Dec 4 -308.26966 2860.751  -602.481118
Jan 5 -112.42986 2656.377  -303.946709
Feb 5  257.21978 2610.018  -497.237388
Mar 5 1165.20288 2563.659  -888.861525
Apr 5  181.67988 2586.281   -67.961032
May 5  199.82477 2608.904   171.271585
Jun 5  307.80795 2650.013   332.178804
Jul 5  -39.20886 2691.123   648.086011
Aug 5 -138.54966 2733.942   404.607447
Sep 5 -419.55688 2776.762   -27.204692
Oct 5 -653.16205 2805.046    38.115719
Nov 5 -440.55844 2833.331  -422.772651
Dec 5 -308.26966 2862.177  -383.907419
Jan 6 -112.42986 2891.023    51.406784
Feb 6  257.21978 2931.716     1.064595
Mar 6 1165.20288 2972.408  -587.611053
Apr 6  181.67988 3015.219    43.101449
May 6  199.82477 3058.029   192.146076
Jun 6  307.80795 3106.944   155.247834
Jul 6  -39.20886 3155.859   113.349580
Aug 6 -138.54966 3210.151   188.399121
Sep 6 -419.55688 3264.442  -144.884915
> m$win
  s   t   l 
691  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
70  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1usrf1292944480.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2n1801292944480.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3n1801292944480.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/4xt831292944480.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5b2nc1292944480.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6x34i1292944480.tab") 
> 
> try(system("convert tmp/1usrf1292944480.ps tmp/1usrf1292944480.png",intern=TRUE))
character(0)
> try(system("convert tmp/2n1801292944480.ps tmp/2n1801292944480.png",intern=TRUE))
character(0)
> try(system("convert tmp/3n1801292944480.ps tmp/3n1801292944480.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xt831292944480.ps tmp/4xt831292944480.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.996   0.618   2.226