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(1.4816,1.4562,1.4268,1.4088,1.4016,1.3650,1.3190,1.3050,1.2785,1.3239,1.3449,1.2732,1.3322,1.4369,1.4975,1.5770,1.5553,1.5557,1.5750,1.5527,1.4748,1.4718,1.4570,1.4684,1.4227,1.3896,1.3622,1.3716,1.3419,1.3511,1.3516,1.3242,1.3074,1.2999,1.3213,1.2881,1.2611,1.2727,1.2811,1.2684,1.2650,1.2770,1.2271,1.2020,1.1938,1.2103,1.1856,1.1786,1.2015,1.2256,1.2292,1.2037,1.2165,1.2694,1.2938,1.3201,1.3014,1.3119,1.3408,1.2991)
> 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 -0.0087760371 1.422163  0.068212633
Feb 1  0.0097111729 1.412139  0.034349996
Mar 1  0.0149783845 1.402114  0.009707357
Apr 1  0.0219420616 1.393882 -0.007023768
May 1  0.0125257037 1.385649  0.003425141
Jun 1  0.0207472857 1.379068 -0.034815227
Jul 1  0.0110488697 1.372487 -0.064535598
Aug 1  0.0003260343 1.367166 -0.062491553
Sep 1 -0.0275167883 1.361844 -0.055827520
Oct 1 -0.0136787624 1.366840 -0.029260903
Nov 1 -0.0058607343 1.371835 -0.021074289
Dec 1 -0.0354471333 1.390401 -0.081753376
Jan 2 -0.0087760371 1.408966 -0.067989958
Feb 2  0.0097111729 1.429586 -0.002397032
Mar 2  0.0149783845 1.450206  0.032315893
Apr 2  0.0219420616 1.466829  0.088228452
May 2  0.0125257037 1.483453  0.059321046
Jun 2  0.0207472857 1.492522  0.042431084
Jul 2  0.0110488697 1.501590  0.062361119
Aug 2  0.0003260343 1.498054  0.054320136
Sep 2 -0.0275167883 1.494518  0.007799140
Oct 2 -0.0136787624 1.479419  0.006059512
Nov 2 -0.0058607343 1.464321 -0.001460119
Dec 2 -0.0354471333 1.445329  0.058517831
Jan 3 -0.0087760371 1.426338  0.005138286
Feb 3  0.0097111729 1.408502 -0.028613617
Mar 3  0.0149783845 1.390667 -0.043445521
Apr 3  0.0219420616 1.375981 -0.026323396
May 3  0.0125257037 1.361296 -0.031921236
Jun 3  0.0207472857 1.349467 -0.019114332
Jul 3  0.0110488697 1.337639  0.002912569
Aug 3  0.0003260343 1.328577 -0.004703130
Sep 3 -0.0275167883 1.319516  0.015401158
Oct 3 -0.0136787624 1.311798  0.001780615
Nov 3 -0.0058607343 1.304081  0.023080070
Dec 3 -0.0354471333 1.295650  0.027896981
Jan 4 -0.0087760371 1.287220 -0.017343603
Feb 4  0.0097111729 1.277608 -0.014619212
Mar 4  0.0149783845 1.267996 -0.001874823
Apr 4  0.0219420616 1.258446 -0.011988194
May 4  0.0125257037 1.248896  0.003578471
Jun 4  0.0207472857 1.241150  0.015102265
Jul 4  0.0110488697 1.233405 -0.017353942
Aug 4  0.0003260343 1.228061 -0.026386713
Sep 4 -0.0275167883 1.222716 -0.001399497
Oct 4 -0.0136787624 1.218938  0.005040466
Nov 4 -0.0058607343 1.215160 -0.023699572
Dec 4 -0.0354471333 1.215448 -0.001400451
Jan 5 -0.0087760371 1.215735 -0.005458825
Feb 5  0.0097111729 1.222043 -0.006154547
Mar 5  0.0149783845 1.228352 -0.014130270
Apr 5  0.0219420616 1.241035 -0.059277469
May 5  0.0125257037 1.253719 -0.049744633
Jun 5  0.0207472857 1.266073 -0.017420187
Jul 5  0.0110488697 1.278427  0.004324258
Aug 5  0.0003260343 1.291457  0.028317210
Sep 5 -0.0275167883 1.304487  0.024430149
Oct 5 -0.0136787624 1.318299  0.007280035
Nov 5 -0.0058607343 1.332111  0.014549920
Dec 5 -0.0354471333 1.346357 -0.011809730
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/13bgj1259929381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2h87u1259929381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3ov841259929381.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/49mfm1259929381.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5tu471259929381.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6ude91259929381.tab") 
> system("convert tmp/13bgj1259929381.ps tmp/13bgj1259929381.png")
> system("convert tmp/2h87u1259929381.ps tmp/2h87u1259929381.png")
> system("convert tmp/3ov841259929381.ps tmp/3ov841259929381.png")
> system("convert tmp/49mfm1259929381.ps tmp/49mfm1259929381.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.972   0.623   2.873