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(562,561,555,544,537,543,594,611,613,611,594,595,591,589,584,573,567,569,621,629,628,612,595,597,593,590,580,574,573,573,620,626,620,588,566,557,561,549,532,526,511,499,555,565,542,527,510,514,517,508,493,490,469,478,528,534,518,506,502,516,528)
> 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   3.6908252 558.3822  -0.07305895
Feb 1  -3.7599243 561.5199   3.24003570
Mar 1 -13.5951789 564.6575   3.93763537
Apr 1 -20.2371238 567.7757  -3.53856152
May 1 -29.4790644 570.8938  -4.41476265
Jun 1 -27.9471389 573.9184  -2.97125073
Jul 1  23.7847915 576.9430  -6.72774378
Aug 1  33.8421521 579.8327  -2.67482393
Sep 1  25.6995137 582.7224   4.57809492
Oct 1  11.1796329 585.4186  14.40174054
Nov 1  -3.3402441 588.1149   9.22538230
Dec 1   0.1617536 590.1982   4.64002626
Jan 2   3.6908252 592.2816  -4.97240363
Feb 2  -3.7599243 593.5445  -0.78453474
Mar 2 -13.5951789 594.8073   2.78783916
Apr 2 -20.2371238 595.3835  -2.14633735
May 2 -29.4790644 595.9596   0.51948191
Jun 2 -27.9471389 596.2411   0.70599748
Jul 2  23.7847915 596.5227   0.69250806
Aug 2  33.8421521 596.5807  -1.42287843
Sep 2  25.6995137 596.6388   5.66173408
Oct 2  11.1796329 596.6207   4.19971617
Nov 2  -3.3402441 596.6025   1.73769439
Dec 2   0.1617536 596.6207   0.21758716
Jan 3   3.6908252 596.6388  -7.32959392
Feb 3  -3.7599243 596.2726  -2.51270004
Mar 3 -13.5951789 595.9065  -2.31130115
Apr 3 -20.2371238 594.5549  -0.31777807
May 3 -29.4790644 593.2033   9.27574077
Jun 3 -27.9471389 590.6771  10.27004772
Jul 3  23.7847915 588.1509   8.06434969
Aug 3  33.8421521 584.4626   7.69524699
Sep 3  25.6995137 580.7743  13.52614330
Oct 3  11.1796329 575.9606   0.85972359
Nov 3  -3.3402441 571.1469  -1.80669998
Dec 3   0.1617536 565.5660  -8.72775499
Jan 4   3.6908252 559.9851  -2.67588386
Feb 4  -3.7599243 554.4197  -1.65974635
Mar 4 -13.5951789 548.8543  -3.25910383
Apr 4 -20.2371238 543.8665   2.37061002
May 4 -29.4790644 538.8787   1.60031964
Jun 4 -27.9471389 534.7462  -7.79906683
Jul 4  23.7847915 530.6137   0.60154171
Aug 4  33.8421521 527.0898   4.06802524
Sep 4  25.6995137 523.5660  -7.26549223
Oct 4  11.1796329 520.5365  -4.71611313
Nov 4  -3.3402441 517.5070  -4.16673789
Dec 4   0.1617536 515.0385  -1.20022694
Jan 5   3.6908252 512.5700   0.73921016
Feb 5  -3.7599243 510.5004   1.25955247
Mar 5 -13.5951789 508.4308  -1.83560020
Apr 5 -20.2371238 507.2303   3.00681465
May 5 -29.4790644 506.0298  -7.55077474
Jun 5 -27.9471389 506.0328  -0.08570634
Jul 5  23.7847915 506.0359  -1.82064292
Aug 5  33.8421521 506.1474  -5.98951920
Sep 5  25.6995137 506.2589 -13.95839648
Oct 5  11.1796329 506.4309 -11.61056147
Nov 5  -3.3402441 506.6030  -1.26273032
Dec 5   0.1617536 506.9482   8.89003032
Jan 6   3.6908252 507.2935  17.01571710
> m$win
  s   t   l 
611  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
62  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/15j381259934136.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2jjqr1259934136.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3jn1f1259934136.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/4n37m1259934136.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/529ho1259934136.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6ktsh1259934136.tab") 
> system("convert tmp/15j381259934136.ps tmp/15j381259934136.png")
> system("convert tmp/2jjqr1259934136.ps tmp/2jjqr1259934136.png")
> system("convert tmp/3jn1f1259934136.ps tmp/3jn1f1259934136.png")
> system("convert tmp/4n37m1259934136.ps tmp/4n37m1259934136.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.976   0.637   1.190