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(5.7,6.1,6,5.9,5.8,5.7,5.6,5.4,5.4,5.5,5.6,5.7,5.9,6.1,6,5.8,5.8,5.7,5.5,5.3,5.2,5.2,5,5.1,5.1,5.2,4.9,4.8,4.5,4.5,4.4,4.4,4.2,4.1,3.9,3.8,3.9,4.2,4.1,3.8,3.6,3.7,3.5,3.4,3.1,3.1,3.1,3.2,3.3,3.5,3.6,3.5,3.3,3.2,3.1,3.2,3,3,3.1,3.4)
> 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  0.08203130 5.674068 -0.056099318
Feb 1  0.36167990 5.678053  0.060267239
Mar 1  0.30132846 5.682038  0.016633836
Apr 1  0.17236848 5.686820  0.040811175
May 1  0.04340851 5.691603  0.064988502
Jun 1  0.03205770 5.696968 -0.029025877
Jul 1 -0.07929319 5.702333 -0.023040177
Aug 1 -0.12864249 5.706646 -0.178003575
Sep 1 -0.25799183 5.710959 -0.052966933
Oct 1 -0.22063196 5.712232  0.008399822
Nov 1 -0.22327218 5.713506  0.109766656
Dec 1 -0.08304267 5.711879  0.071163951
Jan 2  0.08203130 5.710252  0.107716791
Feb 2  0.36167990 5.698381  0.039938900
Mar 2  0.30132846 5.686510  0.012161048
Apr 2  0.17236848 5.655073 -0.027441543
May 2  0.04340851 5.623636  0.132955853
Jun 2  0.03205770 5.571111  0.096831380
Jul 2 -0.07929319 5.518586  0.060706985
Aug 2 -0.12864249 5.444522 -0.015879055
Sep 2 -0.25799183 5.370457  0.087534944
Oct 2 -0.22063196 5.277390  0.143242448
Nov 2 -0.22327218 5.184322  0.038950030
Dec 2 -0.08304267 5.084561  0.098482057
Jan 3  0.08203130 4.984799  0.033169629
Feb 3  0.36167990 4.892439 -0.054119288
Mar 3  0.30132846 4.800080 -0.201408166
Apr 3  0.17236848 4.711287 -0.083655512
May 3  0.04340851 4.622494 -0.165902871
Jun 3  0.03205770 4.533599 -0.065656548
Jul 3 -0.07929319 4.444703  0.034589854
Aug 3 -0.12864249 4.361401  0.167241521
Sep 3 -0.25799183 4.278099  0.179893226
Oct 3 -0.22063196 4.198545  0.122086478
Nov 3 -0.22327218 4.118992  0.004279807
Dec 3 -0.08304267 4.038212 -0.155169482
Jan 4  0.08203130 3.957432 -0.139463226
Feb 4  0.36167990 3.875862 -0.037541770
Mar 4  0.30132846 3.794292  0.004379726
Apr 4  0.17236848 3.721883 -0.094251617
May 4  0.04340851 3.649474 -0.092882973
Jun 4  0.03205770 3.590803  0.077139023
Jul 4 -0.07929319 3.532132  0.047161098
Aug 4 -0.12864249 3.483715  0.044927595
Sep 4 -0.25799183 3.435298 -0.077305869
Oct 4 -0.22063196 3.397066 -0.076433668
Nov 4 -0.22327218 3.358834 -0.035561389
Dec 4 -0.08304267 3.328946 -0.045903191
Jan 5  0.08203130 3.299058 -0.081089448
Feb 5  0.36167990 3.280351 -0.142031044
Mar 5  0.30132846 3.261644  0.037027398
Apr 5  0.17236848 3.263851  0.063780659
May 5  0.04340851 3.266058 -0.009466094
Jun 5  0.03205770 3.272386 -0.104444143
Jul 5 -0.07929319 3.278715 -0.099422114
Aug 5 -0.12864249 3.286063  0.042579005
Sep 5 -0.25799183 3.293412 -0.035419836
Oct 5 -0.22063196 3.301910 -0.081278465
Nov 5 -0.22327218 3.310409  0.012862984
Dec 5 -0.08304267 3.320074  0.162968540
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1kzuv1259917616.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2yjtq1259917616.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3hfs51259917616.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/4qdoy1259917616.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5u60f1259917616.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/63w6n1259917616.tab") 
> system("convert tmp/1kzuv1259917616.ps tmp/1kzuv1259917616.png")
> system("convert tmp/2yjtq1259917616.ps tmp/2yjtq1259917616.png")
> system("convert tmp/3hfs51259917616.ps tmp/3hfs51259917616.png")
> system("convert tmp/4qdoy1259917616.ps tmp/4qdoy1259917616.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.950   0.602   3.299