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(8.2,8.0,7.5,6.8,6.5,6.6,7.6,8.0,8.1,7.7,7.5,7.6,7.8,7.8,7.8,7.5,7.5,7.1,7.5,7.5,7.6,7.7,7.7,7.9,8.1,8.2,8.2,8.2,7.9,7.3,6.9,6.6,6.7,6.9,7.0,7.1,7.2,7.1,6.9,7.0,6.8,6.4,6.7,6.6,6.4,6.3,6.2,6.5,6.8,6.8,6.4,6.1,5.8,6.1,7.2,7.3,6.9,6.1,5.8,6.2,7.1,7.7,7.9,7.7,7.4,7.5,8.0,8.1)
> 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  0.351821216 7.285286  0.562892323
Feb 1  0.406846050 7.318404  0.274749671
Mar 1  0.245204361 7.351522 -0.096726457
Apr 1  0.005809651 7.383530 -0.589339352
May 1 -0.233585285 7.415537 -0.681952022
Jun 1 -0.394824681 7.440760 -0.445934988
Jul 1  0.077269175 7.465982  0.056748793
Aug 1  0.089158504 7.490262  0.420579400
Sep 1  0.025821591 7.514542  0.559636248
Oct 1 -0.185373225 7.560870  0.324503310
Nov 1 -0.296568194 7.607198  0.189370524
Dec 1 -0.091579025 7.622242  0.069337477
Jan 2  0.351821216 7.637285 -0.189106641
Feb 2  0.406846050 7.615579 -0.222425049
Mar 2  0.245204361 7.593873 -0.039076934
Apr 2  0.005809651 7.585308 -0.091117154
May 2 -0.233585285 7.576742  0.156842851
Jun 2 -0.394824681 7.599006 -0.104181570
Jul 2  0.077269175 7.621270 -0.198539242
Aug 2  0.089158504 7.657535 -0.246693665
Sep 2  0.025821591 7.693800 -0.119621847
Oct 2 -0.185373225 7.734023  0.151350443
Nov 2 -0.296568194 7.774245  0.222322886
Dec 2 -0.091579025 7.785241  0.206338201
Jan 3  0.351821216 7.796236 -0.048057556
Feb 3  0.406846050 7.747946  0.045208330
Mar 3  0.245204361 7.699655  0.255140739
Apr 3  0.005809651 7.618352  0.575838732
May 3 -0.233585285 7.537048  0.596536951
Jun 3 -0.394824681 7.450390  0.244434832
Jul 3  0.077269175 7.363731 -0.541000540
Aug 3  0.089158504 7.267264 -0.756422905
Sep 3  0.025821591 7.170797 -0.496619028
Oct 3 -0.185373225 7.083650  0.001723655
Nov 3 -0.296568194 6.996502  0.300066491
Dec 3 -0.091579025 6.949826  0.241753183
Jan 4  0.351821216 6.903150 -0.054971196
Feb 4  0.406846050 6.876077 -0.182922665
Mar 4  0.245204361 6.849003 -0.194207612
Apr 4  0.005809651 6.804313  0.189877514
May 4 -0.233585285 6.759622  0.273962865
Jun 4 -0.394824681 6.712802  0.082022291
Jul 4  0.077269175 6.665982 -0.043251535
Aug 4  0.089158504 6.622158 -0.111316138
Sep 4  0.025821591 6.578333 -0.204154499
Oct 4 -0.185373225 6.524770 -0.039396939
Nov 4 -0.296568194 6.471207  0.025360775
Dec 4 -0.091579025 6.447530  0.144048911
Jan 5  0.351821216 6.423853  0.024325977
Feb 5  0.406846050 6.444403 -0.051249360
Mar 5  0.245204361 6.464954 -0.310158173
Apr 5  0.005809651 6.479364 -0.385173714
May 5 -0.233585285 6.493774 -0.460189030
Jun 5 -0.394824681 6.504799 -0.009974075
Jul 5  0.077269175 6.515823  0.606907628
Aug 5  0.089158504 6.575916  0.634925902
Sep 5  0.025821591 6.636008  0.238170417
Oct 5 -0.185373225 6.738608 -0.453234345
Nov 5 -0.296568194 6.841207 -0.744638954
Dec 5 -0.091579025 6.967671 -0.676092134
Jan 6  0.351821216 7.094135 -0.345956385
Feb 6  0.406846050 7.219230  0.073923491
Mar 6  0.245204361 7.344326  0.310469890
Apr 6  0.005809651 7.477854  0.216336289
May 6 -0.233585285 7.611382  0.022202913
Jun 6 -0.394824681 7.752866  0.141958192
Jul 6  0.077269175 7.894351  0.028380218
Aug 6  0.089158504 8.040073 -0.029231323
> m$win
  s   t   l 
681  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
69  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1d1wb1259784584.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2akev1259784584.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/30avm1259784584.ps",horizontal=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/4u9c41259784584.ps",horizontal=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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5kxpb1259784584.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6ogoh1259784584.tab") 
> system("convert tmp/1d1wb1259784584.ps tmp/1d1wb1259784584.png")
> system("convert tmp/2akev1259784584.ps tmp/2akev1259784584.png")
> system("convert tmp/30avm1259784584.ps tmp/30avm1259784584.png")
> system("convert tmp/4u9c41259784584.ps tmp/4u9c41259784584.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.978   0.619   2.311