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(8.1,7.7,7.5,7.6,7.8,7.8,7.8,7.5,7.5,7.1,7.5,7.5,7.6,7.7,7.7,7.9,8.1,8.2,8.2,8.2,7.9,7.3,6.9,6.6,6.7,6.9,7,7.1,7.2,7.1,6.9,7,6.8,6.4,6.7,6.6,6.4,6.3,6.2,6.5,6.8,6.8,6.4,6.1,5.8,6.1,7.2,7.3,6.9,6.1,5.8,6.2,7.1,7.7,7.9,7.7,7.4,7.5,8,8.1,8)
> 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 -0.03711396 7.838324  0.298790414
Feb 1 -0.22198945 7.799911  0.122078793
Mar 1 -0.31767484 7.761498  0.056177077
Apr 1 -0.10188884 7.729438 -0.027548732
May 1  0.23389702 7.697377 -0.131274391
Jun 1  0.34786105 7.670472 -0.218333042
Jul 1  0.26182509 7.643567 -0.105391705
Aug 1  0.12463640 7.620841 -0.245477828
Sep 1 -0.09255246 7.598116 -0.005563789
Oct 1 -0.29612970 7.607541 -0.211410943
Nov 1  0.08029305 7.616965 -0.197258098
Dec 1  0.01883712 7.657080 -0.175916905
Jan 2 -0.03711396 7.697195 -0.060080556
Feb 2 -0.22198945 7.739971  0.182018631
Mar 2 -0.31767484 7.782747  0.234927723
Apr 2 -0.10188884 7.791127  0.210761657
May 2  0.23389702 7.799507  0.066595741
Jun 2  0.34786105 7.747529  0.104609473
Jul 2  0.26182509 7.695552  0.242623192
Aug 2  0.12463640 7.612902  0.462461580
Sep 2 -0.09255246 7.530252  0.462300130
Oct 2 -0.29612970 7.444839  0.151290361
Nov 2  0.08029305 7.359426 -0.539719409
Dec 2  0.01883712 7.266809 -0.685646151
Jan 3 -0.03711396 7.174192 -0.437077738
Feb 3 -0.22198945 7.089598  0.032391847
Mar 3 -0.31767484 7.005004  0.312671336
Apr 3 -0.10188884 6.955712  0.246176645
May 3  0.23389702 6.906421  0.059682103
Jun 3  0.34786105 6.875660 -0.123521524
Jul 3  0.26182509 6.844900 -0.206725164
Aug 3  0.12463640 6.798863  0.076500356
Sep 3 -0.09255246 6.752826  0.139726037
Oct 3 -0.29612970 6.707252 -0.011122186
Nov 3  0.08029305 6.661677 -0.041970409
Dec 3  0.01883712 6.621702 -0.040539385
Jan 4 -0.03711396 6.581727 -0.144613205
Feb 4 -0.22198945 6.530718 -0.008728739
Mar 4 -0.31767484 6.479709  0.037965631
Apr 4 -0.10188884 6.453416  0.148472380
May 4  0.23389702 6.427124  0.138979278
Jun 4  0.34786105 6.443987  0.008151780
Jul 4  0.26182509 6.460851 -0.322675730
Aug 4  0.12463640 6.473914 -0.498550879
Sep 4 -0.09255246 6.486978 -0.594425865
Oct 4 -0.29612970 6.499248 -0.103118559
Nov 4  0.08029305 6.511518  0.608188746
Dec 4  0.01883712 6.575460  0.705702652
Jan 5 -0.03711396 6.639402  0.297711712
Feb 5 -0.22198945 6.744556 -0.422566143
Mar 5 -0.31767484 6.849709 -0.732034094
Apr 5 -0.10188884 6.963396 -0.661507626
May 5  0.23389702 7.077084 -0.210981009
Jun 5  0.34786105 7.200566  0.151573329
Jul 5  0.26182509 7.324047  0.314127654
Aug 5  0.12463640 7.454370  0.120993181
Sep 5 -0.09255246 7.584694 -0.092141130
Oct 5 -0.29612970 7.721117  0.075012584
Nov 5  0.08029305 7.857541  0.062166298
Dec 5  0.01883712 7.997670  0.083492383
Jan 6 -0.03711396 8.137800 -0.100686378
> m$win
  s   t   l 
611  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
62  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1fqfz1259864120.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2hbdw1259864120.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/392rr1259864120.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/4fnq01259864120.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5hoqb1259864120.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6xl8t1259864120.tab") 
> 
> system("convert tmp/1fqfz1259864120.ps tmp/1fqfz1259864120.png")
> system("convert tmp/2hbdw1259864120.ps tmp/2hbdw1259864120.png")
> system("convert tmp/392rr1259864120.ps tmp/392rr1259864120.png")
> system("convert tmp/4fnq01259864120.ps tmp/4fnq01259864120.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.951   0.600   1.144