R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(11.1,10.9,10,9.2,9.2,9.5,9.6,9.5,9.1,8.9,9,10.1,10.3,10.2,9.6,9.2,9.3,9.4,9.4,9.2,9,9,9,9.8,10,9.8,9.3,9,9,9.1,9.1,9.1,9.2,8.8,8.3,8.4,8.1,7.7,7.9,7.9,8,7.9,7.6,7.1,6.8,6.5,6.9,8.2,8.7,8.3,7.9,7.5,7.8,8.3,8.4,8.2,7.7,7.2,7.3,8.1)
> 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  0.72458343 9.984172  0.39124459
Feb 1  0.49876397 9.924242  0.47699429
Mar 1  0.09294463 9.864312  0.04274386
Apr 1 -0.25266994 9.811122 -0.35845250
May 1 -0.11828474 9.757933 -0.43964862
Jun 1  0.08883857 9.707182 -0.29602102
Jul 1  0.09596198 9.656432 -0.15239350
Aug 1 -0.07567272 9.607560 -0.03188729
Sep 1 -0.30730720 9.558688 -0.15138129
Oct 1 -0.56062595 9.543096 -0.08246966
Nov 1 -0.51394487 9.527503 -0.01355786
Dec 1  0.32741286 9.521922  0.25066527
Jan 2  0.72458343 9.516341  0.05907555
Feb 2  0.49876397 9.501552  0.19968442
Mar 2  0.09294463 9.486762  0.02029317
Apr 2 -0.25266994 9.472816 -0.02014647
May 2 -0.11828474 9.458871 -0.04058587
Jun 2  0.08883857 9.441287 -0.13012603
Jul 2  0.09596198 9.423704 -0.11966628
Aug 2 -0.07567272 9.403669 -0.12799646
Sep 2 -0.30730720 9.383634 -0.07632684
Oct 2 -0.56062595 9.364637  0.19598933
Nov 2 -0.51394487 9.345639  0.16830567
Dec 2  0.32741286 9.324529  0.14805820
Jan 3  0.72458343 9.303419 -0.02800213
Feb 3  0.49876397 9.284450  0.01678627
Mar 3  0.09294463 9.265481 -0.05842545
Apr 3 -0.25266994 9.233761  0.01890921
May 3 -0.11828474 9.202041 -0.08375590
Jun 3  0.08883857 9.116279 -0.10511790
Jul 3  0.09596198 9.030518 -0.02647999
Aug 3 -0.07567272 8.899260  0.27641260
Sep 3 -0.30730720 8.768002  0.73930497
Oct 3 -0.56062595 8.639263  0.72136262
Nov 3 -0.51394487 8.510524  0.30342045
Dec 3  0.32741286 8.380577 -0.30798941
Jan 4  0.72458343 8.250629 -0.87521212
Feb 4  0.49876397 8.095389 -0.89415328
Mar 4  0.09294463 7.940150 -0.13309456
Apr 4 -0.25266994 7.807966  0.34470421
May 4 -0.11828474 7.675782  0.44250322
Jun 4  0.08883857 7.631296  0.17986583
Jul 4  0.09596198 7.586810 -0.08277166
Aug 4 -0.07567272 7.589762 -0.41408905
Sep 4 -0.30730720 7.592714 -0.48540665
Oct 4 -0.56062595 7.597085 -0.53645927
Nov 4 -0.51394487 7.601457 -0.18751173
Dec 4  0.32741286 7.642214  0.23037291
Jan 5  0.72458343 7.682972  0.29244470
Feb 5  0.49876397 7.757891  0.04334465
Mar 5  0.09294463 7.832811 -0.02575552
Apr 5 -0.25266994 7.862667 -0.10999662
May 5 -0.11828474 7.892522  0.02576252
Jun 5  0.08883857 7.914069  0.29709283
Jul 5  0.09596198 7.935615  0.36842304
Aug 5 -0.07567272 7.954906  0.32076686
Sep 5 -0.30730720 7.974197  0.03311046
Oct 5 -0.56062595 7.988470 -0.22784412
Nov 5 -0.51394487 8.002743 -0.18879853
Dec 5  0.32741286 8.012015 -0.23942787
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/12p391259846874.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2xat61259846874.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3lifn1259846874.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/4jh7m1259846874.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5qen21259846874.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6o7rq1259846874.tab") 
> 
> system("convert tmp/12p391259846874.ps tmp/12p391259846874.png")
> system("convert tmp/2xat61259846874.ps tmp/2xat61259846874.png")
> system("convert tmp/3lifn1259846874.ps tmp/3lifn1259846874.png")
> system("convert tmp/4jh7m1259846874.ps tmp/4jh7m1259846874.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.974   0.612   1.321