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(6.3,6.2,6.1,6.3,6.5,6.6,6.5,6.2,6.2,5.9,6.1,6.1,6.1,6.1,6.1,6.4,6.7,6.9,7,7,6.8,6.4,5.9,5.5,5.5,5.6,5.8,5.9,6.1,6.1,6,6,5.9,5.5,5.6,5.4,5.2,5.2,5.2,5.5,5.8,5.8,5.5,5.3,5.1,5.2,5.8,5.8,5.5,5,4.9,5.3,6.1,6.5,6.8,6.6,6.4,6.4,6.6)
> 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 -0.255846341 6.436550  0.119296593
Feb 1 -0.354688321 6.403674  0.151014033
Mar 1 -0.353530383 6.370799  0.082731556
Apr 1 -0.096654259 6.343551  0.053103409
May 1  0.260221782 6.316303 -0.076524654
Jun 1  0.395745007 6.293930 -0.089674734
Jul 1  0.371268232 6.271557 -0.142824813
Aug 1  0.230562299 6.251601 -0.282163187
Sep 1  0.089856230 6.231645 -0.121501423
Oct 1 -0.116353555 6.233685 -0.217331170
Nov 1 -0.002563339 6.235724 -0.133160917
Dec 1 -0.168017091 6.271108 -0.003091167
Jan 2 -0.255846341 6.306492  0.049354081
Feb 2 -0.354688321 6.355895  0.098793277
Mar 2 -0.353530383 6.405298  0.048232556
Apr 2 -0.096654259 6.432291  0.064363351
May 2  0.260221782 6.459284 -0.019505771
Jun 2  0.395745007 6.437666  0.066589026
Jul 2  0.371268232 6.416048  0.212683823
Aug 2  0.230562299 6.368727  0.400710944
Sep 2  0.089856230 6.321406  0.388738201
Oct 2 -0.116353555 6.265923  0.250430245
Nov 2 -0.002563339 6.210441 -0.307877712
Dec 2 -0.168017091 6.139607 -0.471589488
Jan 3 -0.255846341 6.068772 -0.312925766
Feb 3 -0.354688321 5.996209 -0.041520246
Mar 3 -0.353530383 5.923645  0.229885357
Apr 3 -0.096654259 5.875067  0.121587251
May 3  0.260221782 5.826489  0.013289227
Jun 3  0.395745007 5.796070 -0.091814939
Jul 3  0.371268232 5.765651 -0.136919105
Aug 3  0.230562299 5.730535  0.038902638
Sep 3  0.089856230 5.695419  0.114724517
Oct 3 -0.116353555 5.662120 -0.045766913
Nov 3 -0.002563339 5.628822 -0.026258343
Dec 3 -0.168017091 5.596173 -0.028156119
Jan 4 -0.255846341 5.563525 -0.107678397
Feb 4 -0.354688321 5.519956  0.034732696
Mar 4 -0.353530383 5.476387  0.077143872
Apr 4 -0.096654259 5.448317  0.148337289
May 4  0.260221782 5.420247  0.119530789
Jun 4  0.395745007 5.422561 -0.018305800
Jul 4  0.371268232 5.424874 -0.296142388
Aug 4  0.230562299 5.428566 -0.359128343
Sep 4  0.089856230 5.432258 -0.422114159
Oct 4 -0.116353555 5.443336 -0.126982310
Nov 4 -0.002563339 5.454414  0.348149540
Dec 4 -0.168017091 5.510411  0.457606330
Jan 5 -0.255846341 5.566408  0.189438618
Feb 5 -0.354688321 5.661447 -0.306758861
Mar 5 -0.353530383 5.756487 -0.502956257
Apr 5 -0.096654259 5.854174 -0.457519819
May 5  0.260221782 5.951862 -0.112083299
Jun 5  0.395745007 6.049795  0.054460281
Jul 5  0.371268232 6.147728  0.281003861
Aug 5  0.230562299 6.250252  0.119185245
Sep 5  0.089856230 6.352777 -0.042633233
Oct 5 -0.116353555 6.459600  0.056753069
Nov 5 -0.002563339 6.566424  0.036139371
> m$win
  s   t   l 
591  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
60  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/12nsq1259947125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/24x5p1259947125.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3l2rx1259947125.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/438j61259947125.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5opum1259947125.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/651141259947125.tab") 
> system("convert tmp/12nsq1259947125.ps tmp/12nsq1259947125.png")
> system("convert tmp/24x5p1259947125.ps tmp/24x5p1259947125.png")
> system("convert tmp/3l2rx1259947125.ps tmp/3l2rx1259947125.png")
> system("convert tmp/438j61259947125.ps tmp/438j61259947125.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.954   0.617   1.452