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(101.3,106.3,94,102.8,102,105.1,92.4,81.4,105.8,120.3,100.7,88.8,94.3,99.9,103.4,103.3,98.8,104.2,91.2,74.7,108.5,114.5,96.9,89.6,97.1,100.3,122.6,115.4,109,129.1,102.8,96.2,127.7,128.9,126.5,119.8,113.2,114.1,134.1,130,121.8,132.1,105.3,103,117.1,126.3,138.1,119.5,138,135.5,178.6,162.2,176.9,204.9,132.2,142.5,164.3,174.9,175.4,143)
> 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  -5.109465  99.20197   7.20749276
Feb 1  -3.728656  99.30242  10.72623977
Mar 1  10.532152  99.40286 -15.93501302
Apr 1   6.072658  99.48622  -2.75888125
May 1   4.373158  99.56958  -1.94274296
Jun 1  17.009781  99.57723 -11.48701423
Jul 1 -14.033586  99.58488   6.84870343
Aug 1 -20.270320  99.60066   2.06966063
Sep 1   3.832953  99.61644   2.35061141
Oct 1  10.678044  99.81586   9.80609957
Nov 1   3.763142 100.01528  -3.07842013
Dec 1 -13.119869  99.70646   2.21340943
Jan 2  -5.109465  99.39764   0.01182406
Feb 2  -3.728656  98.99830   4.63035850
Mar 2  10.532152  98.59895  -5.73110687
Apr 2   6.072658  98.37118  -1.14384208
May 2   4.373158  98.14341  -3.71657077
Jun 2  17.009781  98.21715 -11.02692948
Jul 2 -14.033586  98.29089   6.94270075
Aug 2 -20.270320  98.89526  -3.92494000
Sep 2   3.832953  99.49963   5.16741284
Oct 2  10.678044 100.60783   3.21412316
Nov 2   3.763142 101.71603  -8.57917439
Dec 2 -13.119869 103.04209  -0.32221662
Jan 3  -5.109465 104.36814  -2.15867378
Feb 3  -3.728656 105.87864  -1.84998202
Mar 3  10.532152 107.38914   4.67870993
Apr 3   6.072658 109.24042   0.08692429
May 3   4.373158 111.09170  -6.46485483
Jun 3  17.009781 113.01206  -0.92183668
Jul 3 -14.033586 114.93242   1.90117040
Aug 3 -20.270320 116.43574   0.03457712
Sep 3   3.832953 117.93907   5.92797742
Oct 3  10.678044 118.97403  -0.75207395
Nov 3   3.763142 120.00899   2.72786680
Dec 3 -13.119869 120.51373  12.40613963
Jan 4  -5.109465 121.01847  -2.70900248
Feb 4  -3.728656 120.93587  -3.10721846
Mar 4  10.532152 120.85328   2.71456575
Apr 4   6.072658 120.76134   3.16600191
May 4   4.373158 120.66940  -3.24255540
Jun 4  17.009781 121.36234  -6.27211581
Jul 4 -14.033586 122.05527  -2.72168730
Aug 4 -20.270320 124.16777  -0.89745154
Sep 4   3.832953 126.28027 -13.01322220
Oct 4  10.678044 129.91268 -14.29072774
Nov 4   3.763142 133.54510   0.79175886
Dec 4 -13.119869 138.02160  -5.40173499
Jan 5  -5.109465 142.49811   0.61135624
Feb 5  -3.728656 146.66187  -7.43321042
Mar 5  10.532152 150.82562  17.24222311
Apr 5   6.072658 153.32228   2.80505769
May 5   4.373158 155.81894  16.70789879
Jun 5  17.009781 158.15436  29.73585968
Jul 5 -14.033586 160.48978 -14.25619050
Aug 5 -20.270320 162.59608   0.17424064
Sep 5   3.832953 164.70238  -4.23533463
Oct 5  10.678044 166.51688  -2.29492296
Nov 5   3.763142 168.33138   3.30548084
Dec 5 -13.119869 169.93611 -13.81624084
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/161io1259772769.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2qn2c1259772769.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/37v7q1259772769.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/4gpp41259772769.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/55a931259772769.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/66wty1259772769.tab") 
> system("convert tmp/161io1259772769.ps tmp/161io1259772769.png")
> system("convert tmp/2qn2c1259772769.ps tmp/2qn2c1259772769.png")
> system("convert tmp/37v7q1259772769.ps tmp/37v7q1259772769.png")
> system("convert tmp/4gpp41259772769.ps tmp/4gpp41259772769.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.932   0.604   1.277