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(8,8.1,7.7,7.5,7.6,7.8,7.8,7.8,7.5,7.5,7.1,7.5,7.5,7.6,7.7,7.7,7.9,8.1,8.2,8.2,8.2,7.9,7.3,6.9,6.6,6.7,6.9,7,7.1,7.2,7.1,6.9,7,6.8,6.4,6.7,6.6,6.4,6.3,6.2,6.5,6.8,6.8,6.4,6.1,5.8,6.1,7.2,7.3,6.9,6.1,5.8,6.2,7.1,7.7,7.9,7.7,7.4,7.5,8)
> 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  0.009275983 7.944682  0.046041797
Feb 1 -0.040243253 7.893960  0.246283717
Mar 1 -0.229762214 7.843237  0.086525362
Apr 1 -0.327955572 7.798295  0.029660500
May 1 -0.106149113 7.753353 -0.047204179
Jun 1  0.230889002 7.713562 -0.144450534
Jul 1  0.347927142 7.673770 -0.221696916
Aug 1  0.270021690 7.636910 -0.106931885
Sep 1  0.132116513 7.600051 -0.232167129
Oct 1 -0.085656567 7.593380 -0.007723544
Nov 1 -0.283429660 7.586710 -0.203279946
Dec 1  0.082966215 7.620652 -0.203618623
Jan 2  0.009275983 7.654595 -0.163871192
Feb 2 -0.040243253 7.698893 -0.058650002
Mar 2 -0.229762214 7.743191  0.186570913
Apr 2 -0.327955572 7.774765  0.253190791
May 2 -0.106149113 7.806338  0.199810851
Jun 2  0.230889002 7.783507  0.085604302
Jul 2  0.347927142 7.760675  0.091397727
Aug 2  0.270021690 7.687516  0.242462364
Sep 2  0.132116513 7.614357  0.453526726
Oct 2 -0.085656567 7.529604  0.456053013
Nov 2 -0.283429660 7.444850  0.138579313
Dec 2  0.082966215 7.356796 -0.539762479
Jan 3  0.009275983 7.268742 -0.678018163
Feb 3 -0.040243253 7.176442 -0.436198571
Mar 3 -0.229762214 7.084141  0.045620746
Apr 3 -0.327955572 7.015431  0.312524967
May 3 -0.106149113 6.946720  0.259429370
Jun 3  0.230889002 6.911684  0.057427313
Jul 3  0.347927142 6.876648 -0.124574771
Aug 3  0.270021690 6.839203 -0.209224606
Sep 3  0.132116513 6.801758  0.066125285
Oct 3 -0.085656567 6.752593  0.133063913
Nov 3 -0.283429660 6.703427 -0.019997446
Dec 3  0.082966215 6.663493 -0.046459505
Jan 4  0.009275983 6.623559 -0.032835457
Feb 4 -0.040243253 6.578149 -0.137905512
Mar 4 -0.229762214 6.532738 -0.002975841
Apr 4 -0.327955572 6.486905  0.041050310
May 4 -0.106149113 6.441072  0.165076643
Jun 4  0.230889002 6.439714  0.129396987
Jul 4  0.347927142 6.438356  0.013717305
Aug 4  0.270021690 6.458252 -0.328274049
Sep 4  0.132116513 6.478149 -0.510265677
Oct 4 -0.085656567 6.484885 -0.599228929
Nov 4 -0.283429660 6.491622 -0.108192168
Dec 4  0.082966215 6.525720  0.591313408
Jan 5  0.009275983 6.559819  0.730905091
Feb 5 -0.040243253 6.650792  0.289450822
Mar 5 -0.229762214 6.741766 -0.412003721
Apr 5 -0.327955572 6.858795 -0.730839544
May 5 -0.106149113 6.975824 -0.669675184
Jun 5  0.230889002 7.087998 -0.218887222
Jul 5  0.347927142 7.200172  0.151900713
Aug 5  0.270021690 7.316746  0.313231937
Sep 5  0.132116513 7.433321  0.134562886
Oct 5 -0.085656567 7.556632 -0.070975670
Nov 5 -0.283429660 7.679944  0.103485786
Dec 5  0.082966215 7.807799  0.109234948
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1sj3p1260545414.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2njqq1260545414.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/37dzo1260545414.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/4t8mz1260545414.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/52bff1260545414.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6kqnl1260545414.tab") 
> system("convert tmp/1sj3p1260545414.ps tmp/1sj3p1260545414.png")
> system("convert tmp/2njqq1260545414.ps tmp/2njqq1260545414.png")
> system("convert tmp/37dzo1260545414.ps tmp/37dzo1260545414.png")
> system("convert tmp/4t8mz1260545414.ps tmp/4t8mz1260545414.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.976   0.628   1.831