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(100,96.21064363,96.31280765,107.1793443,114.9066592,92.56060184,114.9995356,107.1236185,117.7765394,107.3650971,106.2970187,114.5072908,98.0031578,103.0649206,100.2879168,104.6066685,111.1544534,104.9874617,109.9284852,111.5352466,132.4974459,100.3436426,123.0983561,114.2379493,104.569518,109.0833101,106.9843039,133.6769759,124.8537197,122.5132349,116.8013374,116.0118882,129.7575926,125.1973623,143.7912139,127.9465032,130.2962757,108.4424631,129.3675118,143.6797622,131.8844618,117.6186496,118.9560695,104.8202842,134.624315,140.401226,143.8005015,153.4317823,153.2924677,127.3149438,153.5525216,136.9276493,131.7730101,144.3391845,107.4208229,113.6249652,124.2221603,102.0618557,96.36853348,111.6838488)
> 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 -1.228273 103.0408  -1.81253672
Feb 1 -9.839254 103.6300   2.41994241
Mar 1 -1.563463 104.2191  -6.34282993
Apr 1  6.517436 104.7001  -4.03823332
May 1  4.385634 105.1812   5.33984301
Jun 1 -2.145831 105.5620 -10.85558093
Jul 1 -4.949233 105.9428  14.00592447
Aug 1 -7.966585 106.3169   8.77326295
Sep 1  9.166529 106.6910   1.91897367
Oct 1 -3.363486 106.8512   3.87736637
Nov 1  4.405566 107.0114  -5.11994510
Dec 1  6.580950 106.9106   1.01574481
Jan 2 -1.228273 106.8098  -7.57836446
Feb 2 -9.839254 107.0975   5.80670043
Mar 2 -1.563463 107.3852  -5.53377314
Apr 2  6.517436 108.0670  -9.97772439
May 2  4.385634 108.7488  -1.97994097
Jun 2 -2.145831 109.4359  -2.30260162
Jul 2 -4.949233 110.1230   4.75469114
Aug 2 -7.966585 110.8914   8.61043672
Sep 2  9.166529 111.6598  11.67115445
Oct 2 -3.363486 112.7085  -9.00133470
Nov 2  4.405566 113.7572   4.93562489
Dec 2  6.580950 114.6873  -7.03025116
Jan 3 -1.228273 115.6173  -9.81954578
Feb 3 -9.839254 116.4034   2.51915333
Mar 3 -1.563463 117.1895  -8.64171773
Apr 3  6.517436 118.4716   8.68790994
May 3  4.385634 119.7538   0.71431088
Jun 3 -2.145831 121.2612   3.39789682
Jul 3 -4.949233 122.7686  -1.01799173
Aug 3 -7.966585 123.9352   0.04331232
Sep 3  9.166529 125.1018  -4.51069579
Oct 3 -3.363486 125.8468   2.71404210
Nov 3  4.405566 126.5919  12.79379382
Dec 3  6.580950 126.8241  -5.45851935
Jan 4 -1.228273 127.0563   4.46825661
Feb 4 -9.839254 126.9346  -8.65285402
Mar 4 -1.563463 126.8128   4.11812478
Apr 4  6.517436 127.1326  10.02973435
May 4  4.385634 127.4523   0.04649458
Jun 4 -2.145831 128.6765  -8.91204076
Jul 4 -4.949233 129.9007  -5.99540578
Aug 4 -7.966585 131.5514 -18.76456092
Sep 4  9.166529 133.2022  -7.74436572
Oct 4 -3.363486 134.4993   9.26542328
Nov 4  4.405566 135.7964   3.59850872
Dec 4  6.580950 136.6012  10.24965326
Jan 5 -1.228273 137.4059  17.11480833
Feb 5 -9.839254 136.8835   0.27071842
Mar 5 -1.563463 136.3610  18.75495834
Apr 5  6.517436 132.7490  -2.33876763
May 5  4.385634 129.1369  -1.74955903
Jun 5 -2.145831 125.3834  21.10164164
Jul 5 -4.949233 121.6298  -9.25975547
Aug 5 -7.966585 117.6862   3.90532898
Sep 5  9.166529 113.7426   1.31300047
Oct 5 -3.363486 109.5835  -4.15812550
Nov 5  4.405566 105.4243 -13.46133716
Dec 5  6.580950 101.1164   3.98653533
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/13d8s1259944460.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2kwoc1259944460.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3cmyo1259944460.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/4ih581259944460.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5ohwf1259944460.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6e2n81259944460.tab") 
> 
> system("convert tmp/13d8s1259944460.ps tmp/13d8s1259944460.png")
> system("convert tmp/2kwoc1259944460.ps tmp/2kwoc1259944460.png")
> system("convert tmp/3cmyo1259944460.ps tmp/3cmyo1259944460.png")
> system("convert tmp/4ih581259944460.ps tmp/4ih581259944460.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.972   0.644   1.163