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(102.86,102.55,102.28,102.26,102.57,103.08,102.76,102.51,102.87,103.14,103.12,103.16,102.48,102.57,102.88,102.63,102.38,101.69,101.96,102.19,101.87,101.6,101.63,101.22,101.21,101.49,101.64,101.66,101.77,101.82,101.78,101.28,101.29,101.37,101.12,101.51,102.24,102.94,103.09,103.46,103.64,104.39,104.15,105.21,105.8,105.91,105.39,105.46,104.72,103.14,102.63,102.32,101.93,100.62,100.6,99.63,98.9,98.32,99.22,98.81)
> 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  0.07318921 102.56134  0.225471460
Feb 1 -0.04377718 102.59266  0.001112589
Mar 1 -0.03074394 102.62399 -0.313245914
Apr 1 -0.02093190 102.65112 -0.370184018
May 1  0.01888006 102.67824 -0.127122056
Jun 1 -0.06894992 102.70078  0.448165216
Jul 1 -0.08878005 102.72333  0.125452636
Aug 1 -0.09993614 102.74574 -0.135799621
Sep 1 -0.04309245 102.76814  0.144948344
Oct 1 -0.01386321 102.77627  0.377590574
Nov 1  0.12136560 102.78440  0.214233245
Dec 1  0.19664012 102.73555  0.227806442
Jan 2  0.07318921 102.68671 -0.279894941
Feb 2 -0.04377718 102.60764  0.006139417
Mar 2 -0.03074394 102.52857  0.382174142
Apr 2 -0.02093190 102.42176  0.229174480
May 2  0.01888006 102.31495  0.046174884
Jun 2 -0.06894992 102.18837 -0.429419631
Jul 2 -0.08878005 102.06179 -0.013013999
Aug 2 -0.09993614 101.94814  0.341792864
Sep 2 -0.04309245 101.83449  0.078599949
Oct 2 -0.01386321 101.75801 -0.144149713
Nov 2  0.12136560 101.68153 -0.172898935
Dec 2  0.19664012 101.64674 -0.623380049
Jan 3  0.07318921 101.61195 -0.475135743
Feb 3 -0.04377718 101.58804 -0.054259535
Mar 3 -0.03074394 101.56413  0.106617039
Apr 3 -0.02093190 101.54983  0.131104664
May 3  0.01888006 101.53553  0.215592356
Jun 3 -0.06894992 101.55311  0.335838830
Jul 3 -0.08878005 101.57069  0.298085452
Aug 3 -0.09993614 101.64402 -0.264082006
Sep 3 -0.04309245 101.71734 -0.384249243
Oct 3 -0.01386321 101.85477 -0.470902007
Nov 3  0.12136560 101.99219 -0.993554331
Dec 3  0.19664012 102.20852 -0.895159558
Jan 4  0.07318921 102.42485 -0.258039364
Feb 4 -0.04377718 102.74239  0.241383832
Mar 4 -0.03074394 103.05994  0.060807396
Apr 4 -0.02093190 103.43009  0.050837121
May 4  0.01888006 103.80025 -0.179133088
Jun 4 -0.06894992 104.09502  0.363929479
Jul 4 -0.08878005 104.38979 -0.151007807
Aug 4 -0.09993614 104.49399  0.815943876
Sep 4 -0.04309245 104.59820  1.244895782
Oct 4 -0.01386321 104.50244  1.421425829
Nov 4  0.12136560 104.40668  0.861956318
Dec 4  0.19664012 104.11480  1.148561789
Jan 5  0.07318921 103.82292  0.823892680
Feb 5 -0.04377718 103.34484 -0.161063771
Mar 5 -0.03074394 102.86676 -0.206019855
Apr 5 -0.02093190 102.29829  0.042638044
May 5  0.01888006 101.72982  0.181296010
Jun 5 -0.06894992 101.17940 -0.490447299
Jul 5 -0.08878005 100.62897  0.059809540
Aug 5 -0.09993614 100.07774 -0.347803459
Sep 5 -0.04309245  99.52651 -0.583416236
Oct 5 -0.01386321  98.97694 -0.643077144
Nov 5  0.12136560  98.42737  0.671262388
Dec 5  0.19664012  97.88311  0.730252983
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1uznt1260464859.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2dz3a1260464859.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/359pj1260464859.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/4yrqw1260464859.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/551251260464859.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6ojhu1260464859.tab") 
> system("convert tmp/1uznt1260464859.ps tmp/1uznt1260464859.png")
> system("convert tmp/2dz3a1260464859.ps tmp/2dz3a1260464859.png")
> system("convert tmp/359pj1260464859.ps tmp/359pj1260464859.png")
> system("convert tmp/4yrqw1260464859.ps tmp/4yrqw1260464859.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.004   0.618   2.166