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(0.6348,0.634,0.62915,0.62168,0.61328,0.6089,0.60857,0.62672,0.62291,0.62393,0.61838,0.62012,0.61659,0.6116,0.61573,0.61407,0.62823,0.64405,0.6387,0.63633,0.63059,0.62994,0.63709,0.64217,0.65711,0.66977,0.68255,0.68902,0.71322,0.70224,0.70045,0.69919,0.69693,0.69763,0.69278,0.70196,0.69215,0.6769,0.67124,0.66532,0.67157,0.66428,0.66576,0.66942,0.6813,0.69144,0.69862,0.695,0.69867,0.68968,0.69233,0.68293,0.68399,0.66895,0.68756,0.68527,0.6776,0.68137,0.67933,0.67922)
> 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  0.0025799851 0.6287099  3.510099e-03
Feb 1 -0.0017251989 0.6273729  8.352345e-03
Mar 1 -0.0007463824 0.6260358  3.860590e-03
Apr 1 -0.0049454456 0.6248171  1.808369e-03
May 1  0.0019054970 0.6235984 -1.222386e-02
Jun 1 -0.0030766081 0.6224026 -1.042597e-02
Jul 1 -0.0011607222 0.6212068 -1.147608e-02
Aug 1  0.0014736812 0.6199878  5.258493e-03
Sep 1 -0.0005899079 0.6187689  4.731056e-03
Oct 1  0.0017474695 0.6185137  3.668794e-03
Nov 1  0.0014668494 0.6182586 -1.345471e-03
Dec 1  0.0030707860 0.6195802 -2.531012e-03
Jan 2  0.0025799851 0.6209018 -6.891816e-03
Feb 2 -0.0017251989 0.6223922 -9.066955e-03
Mar 2 -0.0007463824 0.6238825 -7.406095e-03
Apr 2 -0.0049454456 0.6253461 -6.330637e-03
May 2  0.0019054970 0.6268097 -4.851844e-04
Jun 2 -0.0030766081 0.6291674  1.795917e-02
Jul 2 -0.0011607222 0.6315252  8.335538e-03
Aug 2  0.0014736812 0.6354867 -6.303391e-04
Sep 2 -0.0005899079 0.6394481 -8.268224e-03
Oct 2  0.0017474695 0.6448705 -1.667800e-02
Nov 2  0.0014668494 0.6502929 -1.466978e-02
Dec 2  0.0030707860 0.6563882 -1.728898e-02
Jan 3  0.0025799851 0.6624835 -7.953437e-03
Feb 3 -0.0017251989 0.6687352  2.759963e-03
Mar 3 -0.0007463824 0.6749870  8.309362e-03
Apr 3 -0.0049454456 0.6806164  1.334904e-02
May 3  0.0019054970 0.6862458  2.506870e-02
Jun 3 -0.0030766081 0.6899479  1.536875e-02
Jul 3 -0.0011607222 0.6936499  7.960799e-03
Aug 3  0.0014736812 0.6942762  3.440163e-03
Sep 3 -0.0005899079 0.6949024  2.617521e-03
Oct 3  0.0017474695 0.6928845  2.997998e-03
Nov 3  0.0014668494 0.6908667  4.464731e-04
Dec 3  0.0030707860 0.6878266  1.106261e-02
Jan 4  0.0025799851 0.6847865  4.783491e-03
Feb 4 -0.0017251989 0.6823189 -3.693721e-03
Mar 4 -0.0007463824 0.6798513 -7.864933e-03
Apr 4 -0.0049454456 0.6787193 -8.453822e-03
May 4  0.0019054970 0.6775872 -7.922716e-03
Jun 4 -0.0030766081 0.6778882 -1.053155e-02
Jul 4 -0.0011607222 0.6781891 -1.126838e-02
Aug 4  0.0014736812 0.6796321 -1.168578e-02
Sep 4 -0.0005899079 0.6810751  8.148167e-04
Oct 4  0.0017474695 0.6828084  6.884082e-03
Nov 4  0.0014668494 0.6845418  1.261135e-02
Dec 4  0.0030707860 0.6857628  6.166418e-03
Jan 5  0.0025799851 0.6869838  9.106229e-03
Feb 5 -0.0017251989 0.6872599  4.145311e-03
Mar 5 -0.0007463824 0.6875360  5.540393e-03
Apr 5 -0.0049454456 0.6864130  1.462426e-03
May 5  0.0019054970 0.6852900 -3.205546e-03
Jun 5 -0.0030766081 0.6840426 -1.201597e-02
Jul 5 -0.0011607222 0.6827951  5.925624e-03
Aug 5  0.0014736812 0.6814857  2.310640e-03
Sep 5 -0.0005899079 0.6801763 -1.986351e-03
Oct 5  0.0017474695 0.6788482  7.743187e-04
Nov 5  0.0014668494 0.6775202  3.429855e-04
Dec 5  0.0030707860 0.6761908 -4.162129e-05
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1iu8m1259927589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2zk7s1259927589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/32vp11259927589.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/4v8ph1259927589.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/56i0m1259927590.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6uc671259927590.tab") 
> system("convert tmp/1iu8m1259927589.ps tmp/1iu8m1259927589.png")
> system("convert tmp/2zk7s1259927589.ps tmp/2zk7s1259927589.png")
> system("convert tmp/32vp11259927589.ps tmp/32vp11259927589.png")
> system("convert tmp/4v8ph1259927589.ps tmp/4v8ph1259927589.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.947   0.606   1.118