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(0.7461,0.7775,0.7790,0.7744,0.7905,0.7719,0.7811,0.7557,0.7637,0.7595,0.7471,0.7615,0.7487,0.7389,0.7337,0.7510,0.7382,0.7159,0.7542,0.7636,0.7433,0.7658,0.7627,0.7480,0.7692,0.7850,0.7913,0.7720,0.7880,0.8070,0.8268,0.8244,0.8487,0.8572,0.8214,0.8827,0.9216,0.8865,0.8816,0.8884,0.9466,0.9180,0.9337,0.9559,0.9626,0.9434,0.8639,0.7996,0.6680,0.6572,0.6928,0.6438,0.6454,0.6873,0.7265,0.7912,0.8114,0.8281,0.8393)
> 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 -0.024035136 0.7986785 -0.0285433769
Feb 1 -0.025811504 0.7934204  0.0098910880
Mar 1 -0.019227873 0.7881623  0.0100655552
Apr 1 -0.029903531 0.7832831  0.0210204053
May 1 -0.014999195 0.7784039  0.0270952623
Jun 1 -0.015915828 0.7741226  0.0136932509
Jul 1  0.009327548 0.7698412  0.0019312318
Aug 1  0.024840839 0.7657580 -0.0348988300
Sep 1  0.034434135 0.7616748 -0.0324088959
Oct 1  0.040857961 0.7577417 -0.0390997079
Nov 1  0.018501766 0.7538087 -0.0252104997
Dec 1  0.001930903 0.7521071  0.0074619911
Jan 2 -0.024035136 0.7504055  0.0223296588
Feb 2 -0.025811504 0.7498997  0.0148118469
Mar 2 -0.019227873 0.7493938  0.0035340374
Apr 2 -0.029903531 0.7487337  0.0321698103
May 2 -0.014999195 0.7480736  0.0051255902
Jun 2 -0.015915828 0.7477169 -0.0159010959
Jul 2  0.009327548 0.7473602 -0.0024877898
Aug 2  0.024840839 0.7493429 -0.0105837168
Sep 2  0.034434135 0.7513255 -0.0424596481
Oct 2  0.040857961 0.7559297 -0.0309876777
Nov 2  0.018501766 0.7605339 -0.0163356871
Dec 2  0.001930903 0.7672233 -0.0211541553
Jan 3 -0.024035136 0.7739126  0.0193225533
Feb 3 -0.025811504 0.7814347  0.0293767634
Mar 3 -0.019227873 0.7889569  0.0215709758
Apr 3 -0.029903531 0.7960258  0.0058777531
May 3 -0.014999195 0.8030947 -0.0000954626
Jun 3 -0.015915828 0.8108310  0.0120848141
Jul 3  0.009327548 0.8185674 -0.0010949169
Aug 3  0.024840839 0.8276342 -0.0280750642
Sep 3  0.034434135 0.8367011 -0.0224352157
Oct 3  0.040857961 0.8474147 -0.0310726914
Nov 3  0.018501766 0.8581284 -0.0552301468
Dec 3  0.001930903 0.8695670  0.0112021155
Jan 4 -0.024035136 0.8810056  0.0646295546
Feb 4 -0.025811504 0.8916953  0.0206162229
Mar 4 -0.019227873 0.9023850 -0.0015571064
Apr 4 -0.029903531 0.9076746  0.0106289801
May 4 -0.014999195 0.9129641  0.0486350735
Jun 4 -0.015915828 0.9066437  0.0272721706
Jul 4  0.009327548 0.9003232  0.0240492601
Aug 4  0.024840839 0.8831229  0.0479362612
Sep 4  0.034434135 0.8659226  0.0622432581
Oct 4  0.040857961 0.8435522  0.0589898449
Nov 4  0.018501766 0.8211818  0.0242164520
Dec 4  0.001930903 0.7988115 -0.0011423812
Jan 5 -0.024035136 0.7764412 -0.0844060376
Feb 5 -0.025811504 0.7645655 -0.0815539971
Mar 5 -0.019227873 0.7526898 -0.0406619542
Apr 5 -0.029903531 0.7500050 -0.0763014528
May 5 -0.014999195 0.7473201 -0.0869209443
Jun 5 -0.015915828 0.7457599 -0.0425440974
Jul 5  0.009327548 0.7441997 -0.0270272582
Aug 5  0.024840839 0.7446094  0.0217497563
Sep 5  0.034434135 0.7450191  0.0319467666
Oct 5  0.040857961 0.7477004  0.0395416828
Nov 5  0.018501766 0.7503816  0.0704166192
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1asz31260373734.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/23qhl1260373734.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3k6901260373734.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/4q9d41260373734.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5rw8p1260373734.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6s9mc1260373734.tab") 
> system("convert tmp/1asz31260373734.ps tmp/1asz31260373734.png")
> system("convert tmp/23qhl1260373734.ps tmp/23qhl1260373734.png")
> system("convert tmp/3k6901260373734.ps tmp/3k6901260373734.png")
> system("convert tmp/4q9d41260373734.ps tmp/4q9d41260373734.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.963   0.612   1.659