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

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> x <- c(107.11,107.57,107.81,108.75,109.43,109.62,109.54,109.53,109.84,109.67,109.79,109.56,110.22,110.40,110.69,110.72,110.89,110.58,110.94,110.91,111.22,111.09,111.00,111.06,111.55,112.32,112.64,112.36,112.04,112.37,112.59,112.89,113.22,112.85,113.06,112.99,113.32,113.74,113.91,114.52,114.96,114.91,115.30,115.44,115.52,116.08,115.94,115.56,115.88,116.66,117.41,117.68,117.85,118.21,118.92,119.03,119.17,118.95,118.92,118.90)
> 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 -0.52935963 107.8166 -0.1772246280
Feb 1 -0.20628971 108.0419 -0.2655762438
Mar 1 -0.05121985 108.2671 -0.4059277890
Apr 1  0.10162428 108.4876  0.1607558838
May 1  0.16846850 108.7081  0.5534394768
Jun 1  0.12869769 108.9281  0.5631701878
Jul 1  0.30492698 109.1482  0.0869008033
Aug 1  0.24913309 109.3690 -0.0881454377
Sep 1  0.32533915 109.5899 -0.0751916317
Oct 1  0.06646758 109.7725 -0.1689621802
Nov 1 -0.11240405 109.9551 -0.0527326686
Dec 1 -0.44538403 110.0826 -0.0772151278
Jan 2 -0.52935963 110.2101  0.5392980353
Feb 2 -0.20628971 110.3233  0.2829641443
Mar 2 -0.05121985 110.4366  0.3046303239
Apr 2  0.10162428 110.5372  0.0811492961
May 2  0.16846850 110.6379  0.0836681886
Jun 2  0.12869769 110.7419 -0.2906043590
Jul 2  0.30492698 110.8460 -0.2108770020
Aug 2  0.24913309 110.9806 -0.3197305095
Sep 2  0.32533915 111.1152 -0.2205839699
Oct 2  0.06646758 111.2695 -0.2459643821
Nov 2 -0.11240405 111.4237 -0.3113447342
Dec 2 -0.44538403 111.5773 -0.0719493910
Jan 3 -0.52935963 111.7309  0.3484415745
Feb 3 -0.20628971 111.8842  0.6421194690
Mar 3 -0.05121985 112.0374  0.6537974342
Apr 3  0.10162428 112.1842  0.0742008899
May 3  0.16846850 112.3309 -0.4593957340
Jun 3  0.12869769 112.4670 -0.2257269085
Jul 3  0.30492698 112.6031 -0.3180581783
Aug 3  0.24913309 112.7441 -0.1032310194
Sep 3  0.32533915 112.8851  0.0095961866
Oct 3  0.06646758 113.0686 -0.2850964578
Nov 3 -0.11240405 113.2522 -0.0797890421
Dec 3 -0.44538403 113.4704 -0.0349790592
Jan 4 -0.52935963 113.6885  0.1608265458
Feb 4 -0.20628971 113.9109  0.0354046776
Mar 4 -0.05121985 114.1332 -0.1720171201
Apr 4  0.10162428 114.3605  0.0578610161
May 4  0.16846850 114.5878  0.2037390725
Jun 4  0.12869769 114.8167 -0.0353585820
Jul 4  0.30492698 115.0455 -0.0504563319
Aug 4  0.24913309 115.2875 -0.0966443705
Sep 4  0.32533915 115.5295 -0.3348323621
Oct 4  0.06646758 115.7909  0.2226523464
Nov 4 -0.11240405 116.0523  0.0001371149
Dec 4 -0.44538403 116.3328 -0.3274321098
Jan 5 -0.52935963 116.6134 -0.2040057124
Feb 5 -0.20628971 116.9053 -0.0389713656
Mar 5 -0.05121985 117.1972  0.2640630518
Apr 5  0.10162428 117.4630  0.1153628198
May 5  0.16846850 117.7289 -0.0473374919
Jun 5  0.12869769 117.9894  0.0918643569
Jul 5  0.30492698 118.2500  0.3650661103
Aug 5  0.24913309 118.5097  0.2712094868
Sep 5  0.32533915 118.7693  0.0753529104
Oct 5  0.06646758 119.0252 -0.1416484470
Nov 5 -0.11240405 119.2811 -0.2486497443
Dec 5 -0.44538403 119.5327 -0.1873055639
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/13cph1259954116.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2xjen1259954116.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3kjd51259954116.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/4jqbs1259954116.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5r5wu1259954116.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6j3p51259954116.tab") 
> system("convert tmp/13cph1259954116.ps tmp/13cph1259954116.png")
> system("convert tmp/2xjen1259954116.ps tmp/2xjen1259954116.png")
> system("convert tmp/3kjd51259954116.ps tmp/3kjd51259954116.png")
> system("convert tmp/4jqbs1259954116.ps tmp/4jqbs1259954116.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.975   0.624   1.146