R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(9.492,8.641,9.793,9.603,9.238,9.535,10.295,9.941,9.984,9.563,8.872,9.302,9.215,8.834,9.998,9.604,9.507,9.718,10.095,9.583,9.883,9.365,8.919,9.449,9.769,9.321,9.939,9.336,10.195,9.464,10.010,10.213,9.563,9.890,9.305,9.391,9.928,8.686,9.843,9.627,10.074,9.503,10.119,10.000,9.313,9.866,9.172,9.241,9.659,8.904,9.755,9.080,9.435,8.971,10.063,9.793,9.454,9.759,8.820,9.403,9.676,8.642,9.402,9.610,9.294,9.448,10.319,9.548,9.801,9.596,8.923,9.746,9.829,9.125,9.782,9.441,9.162,9.915,10.444,10.209,9.985,9.842,9.429,10.132,9.849,9.172,10.313,9.819,9.955,10.048,10.082,10.541,10.208,10.233,9.439,9.963,10.158,9.225,10.474,9.757,10.490,10.281,10.444,10.640,10.695,10.786,9.832,9.747,10.411,9.511,10.402,9.701,10.540,10.112,10.915,11.183,10.384,10.834,9.886,10.216,10.943,9.867,10.203,10.837,10.573,10.647,11.502,10.656,10.866,10.835,9.945,10.331)
> 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  0.11050241  9.493940 -1.124425e-01
Feb  1 -0.71635951  9.499336 -1.419769e-01
Mar  1  0.18196041  9.504733  1.063069e-01
Apr  1 -0.14173368  9.508636  2.360982e-01
May  1  0.03793615  9.512538 -3.124744e-01
Jun  1 -0.04355042  9.515768  6.278290e-02
Jul  1  0.55378120  9.518997  2.222220e-01
Aug  1  0.36628865  9.522861  5.185061e-02
Sep  1  0.16152310  9.526725  2.957522e-01
Oct  1  0.19237964  9.530664 -1.600441e-01
Nov  1 -0.54585484  9.534604 -1.167493e-01
Dec  1 -0.15687310  9.537580 -7.870681e-02
Jan  2  0.11050241  9.540556 -4.360581e-01
Feb  2 -0.71635951  9.534051  1.630819e-02
Mar  2  0.18196041  9.527547  2.884927e-01
Apr  2 -0.14173368  9.525225  2.205088e-01
May  2  0.03793615  9.522903 -5.383893e-02
Jun  2 -0.04355042  9.532036  2.295146e-01
Jul  2  0.55378120  9.541169  4.993082e-05
Aug  2  0.36628865  9.554204 -3.374924e-01
Sep  2  0.16152310  9.567239  1.542383e-01
Oct  2  0.19237964  9.579909 -4.072886e-01
Nov  2 -0.54585484  9.592579 -1.277246e-01
Dec  2 -0.15687310  9.608584 -2.711168e-03
Jan  3  0.11050241  9.624589  3.390845e-02
Feb  3 -0.71635951  9.641598  3.957617e-01
Mar  3  0.18196041  9.658606  9.843318e-02
Apr  3 -0.14173368  9.672393 -1.946597e-01
May  3  0.03793615  9.686180  4.708834e-01
Jun  3 -0.04355042  9.687699 -1.801486e-01
Jul  3  0.55378120  9.689218 -2.329988e-01
Aug  3  0.36628865  9.678402  1.683098e-01
Sep  3  0.16152310  9.667586 -2.661086e-01
Oct  3  0.19237964  9.665581  3.203949e-02
Nov  3 -0.54585484  9.663576  1.872786e-01
Dec  3 -0.15687310  9.666858 -1.189845e-01
Jan  4  0.11050241  9.670139  1.473585e-01
Feb  4 -0.71635951  9.665332 -2.629726e-01
Mar  4  0.18196041  9.660525  5.143716e-04
Apr  4 -0.14173368  9.648176  1.205575e-01
May  4  0.03793615  9.635827  4.002367e-01
Jun  4 -0.04355042  9.623549 -7.699818e-02
Jul  4  0.55378120  9.611270 -4.605125e-02
Aug  4  0.36628865  9.597797  3.591406e-02
Sep  4  0.16152310  9.584325 -4.328476e-01
Oct  4  0.19237964  9.557625  1.159954e-01
Nov  4 -0.54585484  9.530925  1.869295e-01
Dec  4 -0.15687310  9.503102 -1.052286e-01
Jan  5  0.11050241  9.475278  7.321953e-02
Feb  5 -0.71635951  9.458931  1.614286e-01
Mar  5  0.18196041  9.442584  1.304558e-01
Apr  5 -0.14173368  9.431616 -2.098821e-01
May  5  0.03793615  9.420648 -2.358384e-02
Jun  5 -0.04355042  9.413346 -3.987952e-01
Jul  5  0.55378120  9.406044  1.031752e-01
Aug  5  0.36628865  9.404806  2.190500e-02
Sep  5  0.16152310  9.403569 -1.110922e-01
Oct  5  0.19237964  9.411916  1.547045e-01
Nov  5 -0.54585484  9.420263 -5.440771e-02
Dec  5 -0.15687310  9.434006  1.258669e-01
Jan  6  0.11050241  9.447750  1.177477e-01
Feb  6 -0.71635951  9.455144 -9.678484e-02
Mar  6  0.18196041  9.462539 -2.424992e-01
Apr  6 -0.14173368  9.467856  2.838776e-01
May  6  0.03793615  9.473173 -2.171094e-01
Jun  6 -0.04355042  9.488869  2.681240e-03
Jul  6  0.55378120  9.504565  2.606537e-01
Aug  6  0.36628865  9.528378 -3.466664e-01
Sep  6  0.16152310  9.552190  8.728651e-02
Oct  6  0.19237964  9.567040 -1.634192e-01
Nov  6 -0.54585484  9.581889 -1.130338e-01
Dec  6 -0.15687310  9.598293  3.045805e-01
Jan  7  0.11050241  9.614697  1.038009e-01
Feb  7 -0.71635951  9.639335  2.020241e-01
Mar  7  0.18196041  9.663974 -6.393468e-02
Apr  7 -0.14173368  9.689588 -1.068542e-01
May  7  0.03793615  9.715201 -5.911376e-01
Jun  7 -0.04355042  9.738024  2.205266e-01
Jul  7  0.55378120  9.760846  1.293727e-01
Aug  7  0.36628865  9.789753  5.295818e-02
Sep  7  0.16152310  9.818660  4.816610e-03
Oct  7  0.19237964  9.852413 -2.027928e-01
Nov  7 -0.54585484  9.886166  8.868880e-02
Dec  7 -0.15687310  9.906137  3.827364e-01
Jan  8  0.11050241  9.926107 -1.876098e-01
Feb  8 -0.71635951  9.936370 -4.801025e-02
Mar  8  0.18196041  9.946632  1.844075e-01
Apr  8 -0.14173368  9.957393  3.340744e-03
May  8  0.03793615  9.968154 -5.108989e-02
Jun  8 -0.04355042  9.975369  1.161813e-01
Jul  8  0.55378120  9.982584 -4.543657e-01
Aug  8  0.36628865  9.992104  1.826073e-01
Sep  8  0.16152310 10.001624  4.485325e-02
Oct  8  0.19237964 10.018519  2.210162e-02
Nov  8 -0.54585484 10.035414 -5.055898e-02
Dec  8 -0.15687310 10.058420  6.145317e-02
Jan  9  0.11050241 10.081426 -3.392844e-02
Feb  9 -0.71635951 10.108432 -1.670726e-01
Mar  9  0.18196041 10.135438  1.566013e-01
Apr  9 -0.14173368 10.164548 -2.658145e-01
May  9  0.03793615 10.193658  2.584057e-01
Jun  9 -0.04355042 10.215785  1.087653e-01
Jul  9  0.55378120 10.237912 -3.476932e-01
Aug  9  0.36628865 10.246871  2.684080e-02
Sep  9  0.16152310 10.255829  2.776478e-01
Oct  9  0.19237964 10.255817  3.378030e-01
Nov  9 -0.54585484 10.255806  1.220492e-01
Dec  9 -0.15687310 10.257732 -3.538585e-01
Jan 10  0.11050241 10.259658  4.084006e-02
Feb 10 -0.71635951 10.268587 -4.122773e-02
Mar 10  0.18196041 10.277517 -5.747736e-02
Apr 10 -0.14173368 10.290652 -4.479183e-01
May 10  0.03793615 10.303787  1.982767e-01
Jun 10 -0.04355042 10.333214 -1.776631e-01
Jul 10  0.55378120 10.362640 -1.421137e-03
Aug 10  0.36628865 10.395168  4.215430e-01
Sep 10  0.16152310 10.427697 -2.052199e-01
Oct 10  0.19237964 10.459637  1.819835e-01
Nov 10 -0.54585484 10.491577 -5.972209e-02
Dec 10 -0.15687310 10.517342 -1.444693e-01
Jan 11  0.11050241 10.543108  2.893898e-01
Feb 11 -0.71635951 10.559064  2.429518e-02
Mar 11  0.18196041 10.575021 -5.539813e-01
Apr 11 -0.14173368 10.578690  4.000433e-01
May 11  0.03793615 10.582360 -4.729602e-02
Jun 11 -0.04355042 10.584456  1.060947e-01
Jul 11  0.55378120 10.586552  3.616671e-01
Aug 11  0.36628865 10.588365 -2.986532e-01
Sep 11  0.16152310 10.590177  1.142994e-01
Oct 11  0.19237964 10.590551  5.206978e-02
Nov 11 -0.54585484 10.590924 -1.000688e-01
Dec 11 -0.15687310 10.589776 -1.019029e-01
> m$win
   s    t    l 
1321   19   13 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
133   2   2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/rcomp/tmp/13ykj1322600675.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/rcomp/tmp/2zme51322600675.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/rcomp/tmp/3yugh1322600675.ps",horizontal=F,onefile=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/rcomp/tmp/4yo7k1322600675.ps",horizontal=F,onefile=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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/57iv81322600675.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/rcomp/tmp/6ej1e1322600675.tab") 
> 
> try(system("convert tmp/13ykj1322600675.ps tmp/13ykj1322600675.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zme51322600675.ps tmp/2zme51322600675.png",intern=TRUE))
character(0)
> try(system("convert tmp/3yugh1322600675.ps tmp/3yugh1322600675.png",intern=TRUE))
character(0)
> try(system("convert tmp/4yo7k1322600675.ps tmp/4yo7k1322600675.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.130   0.130   2.248