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(15836.8,17570.4,18252.1,16196.7,16643,17729,16446.1,15993.8,16373.5,17842.2,22321.5,22786.7,18274.1,22392.9,23899.3,21343.5,22952.3,21374.4,21164.1,20906.5,17877.4,20664.3,22160,19813.6,17735.4,19640.2,20844.4,19823.1,18594.6,21350.6,18574.1,18924.2,17343.4,19961.2,19932.1,19464.6,16165.4,17574.9,19795.4,19439.5,17170,21072.4,17751.8,17515.5,18040.3,19090.1,17746.5,19202.1,15141.6,16258.1,18586.5,17209.4,17838.7,19123.5,16583.6,15991.2,16704.4,17420.4,17872,17823.2)
> 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 -1978.60795 16082.74  1732.663152
Feb 1    15.74496 16376.09  1178.562535
Mar 1  1541.69741 16669.44    40.962378
Apr 1    21.74866 16993.76  -818.811327
May 1  -187.82104 17318.09  -487.264094
Jun 1  1299.11280 17660.19 -1230.301297
Jul 1  -730.25396 18002.29  -825.937908
Aug 1  -944.91479 18351.85 -1413.132925
Sep 1 -1520.31695 18701.40  -807.586617
Oct 1   214.35386 19150.47 -1522.622588
Nov 1  1231.96278 19599.53  1490.003331
Dec 1  1037.29507 20047.84  1701.562846
Jan 2 -1978.60795 20496.15  -243.442328
Feb 2    15.74496 20802.11  1575.044559
Mar 2  1541.69741 21108.07  1249.531906
Apr 2    21.74866 21202.75   118.998074
May 2  -187.82104 21297.44  1842.685181
Jun 2  1299.11280 21186.56 -1111.277467
Jul 2  -730.25396 21075.69   818.660478
Aug 2  -944.91479 20872.74   978.669893
Sep 2 -1520.31695 20669.80 -1272.079365
Oct 2   214.35386 20448.78     1.165305
Nov 2  1231.96278 20227.77   700.271867
Dec 2  1037.29507 20053.02 -1276.711035
Jan 3 -1978.60795 19878.27  -164.258626
Feb 3    15.74496 19758.36  -133.902064
Mar 3  1541.69741 19638.45  -335.745040
Apr 3    21.74866 19557.84   243.514689
May 3  -187.82104 19477.23  -694.804643
Jun 3  1299.11280 19383.76   667.726526
Jul 3  -730.25396 19290.30    14.058288
Aug 3  -944.91479 19178.85   690.267782
Sep 3 -1520.31695 19067.40  -203.681398
Oct 3   214.35386 18960.88   785.963442
Nov 3  1231.96278 18854.37  -154.229826
Dec 3  1037.29507 18771.70  -344.395364
Jan 4 -1978.60795 18689.03  -545.025591
Feb 4    15.74496 18637.85 -1078.691332
Mar 4  1541.69741 18586.66  -332.956614
Apr 4    21.74866 18548.24   869.507722
May 4  -187.82104 18509.83 -1152.007005
Jun 4  1299.11280 18451.29  1321.995153
Jul 4  -730.25396 18392.76    89.297903
Aug 4  -944.91479 18286.47   173.944691
Sep 4 -1520.31695 18180.18  1380.432806
Oct 4   214.35386 18051.54   824.207494
Nov 4  1231.96278 17922.89 -1408.355927
Dec 4  1037.29507 17799.14   365.663027
Jan 5 -1978.60795 17675.39  -555.182708
Feb 5    15.74496 17570.97 -1328.619152
Mar 5  1541.69741 17466.56  -421.755136
Apr 5    21.74866 17420.05  -232.398090
May 5  -187.82104 17373.54   652.979894
Jun 5  1299.11280 17326.90   497.491285
Jul 5  -730.25396 17280.25    33.603268
Aug 5  -944.91479 17241.60  -305.480597
Sep 5 -1520.31695 17202.94  1021.776864
Oct 5   214.35386 17167.32    38.721780
Nov 5  1231.96278 17131.71  -491.671412
Dec 5  1037.29507 17094.32  -308.413137
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/12cit1259951107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2b43v1259951107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3v1at1259951107.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/4u0ts1259951107.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5mpj01259951107.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6uv211259951107.tab") 
> system("convert tmp/12cit1259951107.ps tmp/12cit1259951107.png")
> system("convert tmp/2b43v1259951107.ps tmp/2b43v1259951107.png")
> system("convert tmp/3v1at1259951107.ps tmp/3v1at1259951107.png")
> system("convert tmp/4u0ts1259951107.ps tmp/4u0ts1259951107.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.946   0.601   1.127