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(161,149,139,135,130,127,122,117,112,113,149,157,157,147,137,132,125,123,117,114,111,112,144,150,149,134,123,116,117,111,105,102,95,93,124,130,124,115,106,105,105,101,95,93,84,87,116,120,117,109,105,107,109,109,108,107,99,103,131,137)
> 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  20.647310 137.0564  3.29632803
Feb 1  10.173178 136.5220  2.30478919
Mar 1   1.699046 135.9877  1.31325088
Apr 1  -1.066341 135.5421  0.52425337
May 1  -2.631725 135.0965 -2.46474636
Jun 1  -5.360756 134.7098 -2.34899857
Jul 1  -9.889787 134.3230 -2.43325079
Aug 1 -12.438605 133.9486 -4.51003720
Sep 1 -18.587424 133.5742 -2.98682347
Oct 1 -17.060804 133.3825 -3.32165719
Nov 1  14.265817 133.1907  1.54350843
Dec 1  20.250095 132.9984  3.75147198
Jan 2  20.647310 132.8062  3.54649919
Feb 2  10.173178 132.4926  4.33420064
Mar 2   1.699046 132.1791  3.12190261
Apr 2  -1.066341 131.7330  1.33334982
May 2  -2.631725 131.2869 -3.65520520
Jun 2  -5.360756 130.6484 -2.28765447
Jul 2  -9.889787 130.0099 -3.12010373
Aug 2 -12.438605 129.1955 -2.75693444
Sep 2 -18.587424 128.3812  1.20623497
Oct 2 -17.060804 127.4789  1.58193816
Nov 2  14.265817 126.5765  3.15764068
Dec 2  20.250095 125.5773  4.17265050
Jan 3  20.647310 124.5780  3.77472399
Feb 3  10.173178 123.3149  0.51193086
Mar 3   1.699046 122.0518 -0.75086175
Apr 3  -1.066341 120.4819 -3.41556942
May 3  -2.631725 118.9120  0.71972069
Jun 3  -5.360756 117.2169 -0.85617392
Jul 3  -9.889787 115.5219 -0.63206853
Aug 3 -12.438605 113.9699  0.46869041
Sep 3 -18.587424 112.4180  1.16944947
Oct 3 -17.060804 111.2041 -1.14332432
Nov 3  14.265817 109.9903 -0.25609876
Dec 3  20.250095 109.0519  0.69804990
Jan 4  20.647310 108.1134 -4.76073777
Feb 4  10.173178 107.3645 -2.53765041
Mar 4   1.699046 106.6155 -2.31456252
Apr 4  -1.066341 106.0032  0.06315952
May 4  -2.631725 105.3908  2.24087934
Jun 4  -5.360756 104.8207  1.54006240
Jul 4  -9.889787 104.2505  0.63924547
Aug 4 -12.438605 103.7901  1.64847806
Sep 4 -18.587424 103.3297 -0.74228921
Oct 4 -17.060804 103.2523  0.80849462
Nov 4  14.265817 103.1749 -1.44072221
Dec 4  20.250095 103.7537 -4.00383495
Jan 5  20.647310 104.3326 -7.97988403
Feb 5  10.173178 105.5335 -6.70668503
Mar 5   1.699046 106.7344 -3.43348551
Apr 5  -1.066341 108.3859 -0.31954136
May 5  -2.631725 110.0373  1.59440057
Jun 5  -5.360756 111.6409  2.71985635
Jul 5  -9.889787 113.2445  4.64531212
Aug 5 -12.438605 114.9125  4.52613107
Sep 5 -18.587424 116.5805  1.00695015
Oct 5 -17.060804 118.2566  1.80417574
Nov 5  14.265817 119.9328 -3.19859934
Dec 5  20.250095 121.5764 -4.82648321
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1o1md1259697609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2ss221259697609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/39f6s1259697609.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/42rgc1259697609.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5xoh91259697609.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6ly941259697609.tab") 
> system("convert tmp/1o1md1259697609.ps tmp/1o1md1259697609.png")
> system("convert tmp/2ss221259697609.ps tmp/2ss221259697609.png")
> system("convert tmp/39f6s1259697609.ps tmp/39f6s1259697609.png")
> system("convert tmp/42rgc1259697609.ps tmp/42rgc1259697609.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.953   0.625   1.339