R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(10570,10297,10635,10872,10296,10383,10431,10574,10653,10805,10872,10625,10407,10463,10556,10646,10702,11353,11346,11451,11964,12574,13031,13812,14544,14931,14886,16005,17064,15168,16050,15839,15137,14954,15648,15305,15579,16348,15928,16171,15937,15713,15594,15683,16438,17032,17696,17745,19394,20148,20108,18584,18441,18391,19178,18079,18483,19644,19195,19650,20830,23595,22937,21814,21928,21777,21383,21467,22052,22680,24320,24977,25204)
> 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  409.29150 10186.64 -2.592700e+01
Feb 1  819.53997 10253.57 -7.761053e+02
Mar 1  515.67567 10320.50 -2.011708e+02
Apr 1  185.76809 10373.90  3.123367e+02
May 1   61.52703 10427.30 -1.928223e+02
Jun 1 -361.28984 10469.34  2.749527e+02
Jul 1 -320.77272 10511.38  2.403938e+02
Aug 1 -643.35760 10549.52  6.678341e+02
Sep 1 -545.44246 10587.67  6.107744e+02
Oct 1 -251.20143 10598.06  4.581429e+02
Nov 1   61.53946 10608.45  2.020117e+02
Dec 1   68.72160 10629.42 -7.313870e+01
Jan 2  409.29150 10650.39 -6.526768e+02
Feb 2  819.53997 10730.92 -1.087461e+03
Mar 2  515.67567 10811.46 -7.711320e+02
Apr 2  185.76809 10982.12 -5.218892e+02
May 2   61.52703 11152.79 -5.123129e+02
Jun 2 -361.28984 11436.77  2.775201e+02
Jul 2 -320.77272 11720.75 -5.398079e+01
Aug 2 -643.35760 12085.79  8.570464e+00
Sep 2 -545.44246 12450.82  5.862170e+01
Oct 2 -251.20143 12861.02 -3.582042e+01
Nov 2   61.53946 13271.22 -3.017624e+02
Dec 2   68.72160 13676.82  6.645573e+01
Jan 3  409.29150 14082.42  5.228611e+01
Feb 3  819.53997 14433.38 -3.219165e+02
Mar 3  515.67567 14784.33 -4.140064e+02
Apr 3  185.76809 15036.36  7.828680e+02
May 3   61.52703 15288.40  1.714076e+03
Jun 3 -361.28984 15436.54  9.274596e+01
Jul 3 -320.77272 15584.69  7.860821e+02
Aug 3 -643.35760 15642.54  8.398182e+02
Sep 3 -545.44246 15700.39 -1.794573e+01
Oct 3 -251.20143 15693.57 -4.883730e+02
Nov 3   61.53946 15686.76 -1.003001e+02
Dec 3   68.72160 15668.60 -4.323261e+02
Jan 4  409.29150 15650.45 -4.807399e+02
Feb 4  819.53997 15695.15 -1.666926e+02
Mar 4  515.67567 15739.86 -3.275325e+02
Apr 4  185.76809 15879.17  1.060624e+02
May 4   61.52703 16018.48 -1.430093e+02
Jun 4 -361.28984 16247.96 -1.736734e+02
Jul 4 -320.77272 16477.44 -5.626715e+02
Aug 4 -643.35760 16770.56 -4.442046e+02
Sep 4 -545.44246 17063.68 -8.023780e+01
Oct 4 -251.20143 17349.02 -6.582309e+01
Nov 4   61.53946 17634.37  9.175024e-02
Dec 4   68.72160 17887.67 -2.113901e+02
Jan 5  409.29150 18140.97  8.437402e+02
Feb 5  819.53997 18353.24  9.752217e+02
Mar 5  515.67567 18565.51  1.026816e+03
Apr 5  185.76809 18724.52 -3.262908e+02
May 5   61.52703 18883.54 -5.040642e+02
Jun 5 -361.28984 19020.55 -2.682642e+02
Jul 5 -320.77272 19157.57  3.412018e+02
Aug 5 -643.35760 19360.99 -6.386315e+02
Sep 5 -545.44246 19564.41 -5.359649e+02
Oct 5 -251.20143 19844.14  5.106144e+01
Nov 5   61.53946 20123.87 -9.904121e+02
Dec 5   68.72160 20415.95 -8.346707e+02
Jan 6  409.29150 20708.03 -2.873171e+02
Feb 6  819.53997 20989.76  1.785696e+03
Mar 6  515.67567 21271.50  1.149822e+03
Apr 6  185.76809 21578.16  5.007106e+01
May 6   61.52703 21884.82 -1.834683e+01
Jun 6 -361.28984 22214.00 -7.570871e+01
Jul 6 -320.77272 22543.18 -8.394046e+02
Aug 6 -643.35760 22861.94 -7.515857e+02
Sep 6 -545.44246 23180.71 -5.832668e+02
Oct 6 -251.20143 23496.17 -5.649729e+02
Nov 6   61.53946 23811.64  4.468212e+02
Dec 6   68.72160 24134.51  7.737662e+02
Jan 7  409.29150 24457.39  3.373235e+02
> 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$outer
[1] 0
> postscript(file="/var/www/html/freestat/rcomp/tmp/1utsr1292971629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/freestat/rcomp/tmp/252au1292971629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/freestat/rcomp/tmp/352au1292971629.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/freestat/rcomp/tmp/4gurf1292971629.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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/5ulo61292971629.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/freestat/rcomp/tmp/6f45u1292971629.tab") 
> 
> try(system("convert tmp/1utsr1292971629.ps tmp/1utsr1292971629.png",intern=TRUE))
character(0)
> try(system("convert tmp/252au1292971629.ps tmp/252au1292971629.png",intern=TRUE))
character(0)
> try(system("convert tmp/352au1292971629.ps tmp/352au1292971629.png",intern=TRUE))
character(0)
> try(system("convert tmp/4gurf1292971629.ps tmp/4gurf1292971629.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.478   0.876   1.604