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(12.6,15.7,13.2,20.3,12.8,8,0.9,3.6,14.1,21.7,24.5,18.9,13.9,11,5.8,15.5,22.4,31.7,30.3,31.4,20.2,19.7,10.8,13.2,15.1,15.6,15.5,12.7,10.9,10,9.1,10.3,16.9,22,27.6,28.9,31,32.9,38.1,28.8,29,21.8,28.8,25.6,28.2,20.2,17.9,16.3,13.2,8.1,4.5,-0.1,0,2.3,2.8,2.9,0.1,3.5,8.6,13.8)
> 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  0.40185208 13.556612  -1.3584636
Feb 1  0.01518888 13.491847   2.1929640
Mar 1 -1.11147327 13.427083   0.8843905
Apr 1 -1.06414578 13.426185   7.9379608
May 1 -1.45681456 13.425287   0.8315275
Jun 1 -1.59318246 13.454719  -3.8615362
Jul 1 -1.84954883 13.484150 -10.7346014
Aug 1 -1.26297234 13.427684  -8.5647119
Sep 1  0.08360343 13.371218   0.6451783
Oct 1  1.91243490 13.537301   6.2502637
Nov 1  2.68126696 13.703384   8.1153486
Dec 1  3.24379148 15.016778   0.6394308
Jan 2  0.40185208 16.330171  -2.8320230
Feb 2  0.01518888 17.792535  -6.8077237
Mar 2 -1.11147327 19.254899 -12.3434255
Apr 2 -1.06414578 19.729222  -3.1650764
May 2 -1.45681456 20.203546   3.6532690
Jun 2 -1.59318246 20.176208  13.1169747
Jul 2 -1.84954883 20.148870  12.0006789
Aug 2 -1.26297234 20.062142  12.6008302
Sep 2  0.08360343 19.975414   0.1409823
Oct 2  1.91243490 19.280249  -1.4926837
Nov 2  2.68126696 18.585083 -10.4663503
Dec 2  3.24379148 17.204558  -7.2483491
Jan 3  0.40185208 15.824032  -1.1258840
Feb 3  0.01518888 14.855490   0.7293211
Mar 3 -1.11147327 13.886948   2.7245251
Apr 3 -1.06414578 14.088300  -0.3241547
May 3 -1.45681456 14.289653  -1.9328382
Jun 3 -1.59318246 15.346361  -3.7531788
Jul 3 -1.84954883 16.403070  -5.4535209
Aug 3 -1.26297234 17.938991  -6.3760190
Sep 3  0.08360343 19.474913  -2.6585163
Oct 3  1.91243490 21.229344  -1.1417786
Nov 3  2.68126696 22.983775   1.9349585
Dec 3  3.24379148 24.578189   1.0780192
Jan 4  0.40185208 26.172604   4.4255439
Feb 4  0.01518888 27.211916   5.6728949
Mar 4 -1.11147327 28.251228  10.9602449
Apr 4 -1.06414578 28.224922   1.6392238
May 4 -1.45681456 28.198616   2.2581989
Jun 4 -1.59318246 27.001338  -3.6081559
Jul 4 -1.84954883 25.804061   4.8454878
Aug 4 -1.26297234 23.747683   3.1152896
Sep 4  0.08360343 21.691304   6.4250922
Oct 4  1.91243490 19.289870  -1.0023051
Nov 4  2.68126696 16.888436  -1.6697029
Dec 4  3.24379148 14.605215  -1.5490060
Jan 5  0.40185208 12.321993   0.4761548
Feb 5  0.01518888 10.308497  -2.2236854
Mar 5 -1.11147327  8.295000  -2.6835267
Apr 5 -1.06414578  7.397135  -6.4329896
May 5 -1.45681456  6.499271  -5.0424562
Jun 5 -1.59318246  5.811455  -1.9182730
Jul 5 -1.84954883  5.123640  -0.4740913
Aug 5 -1.26297234  4.537676  -0.3747035
Sep 5  0.08360343  3.951712  -3.9353150
Oct 5  1.91243490  3.476692  -1.8891273
Nov 5  2.68126696  3.001673   2.9170598
Dec 5  3.24379148  2.623240   7.9329683
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1qrrg1259943837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2bz4d1259943837.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3gp3s1259943837.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/4p8c11259943837.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5h4oi1259943837.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6rq0x1259943837.tab") 
> system("convert tmp/1qrrg1259943837.ps tmp/1qrrg1259943837.png")
> system("convert tmp/2bz4d1259943837.ps tmp/2bz4d1259943837.png")
> system("convert tmp/3gp3s1259943837.ps tmp/3gp3s1259943837.png")
> system("convert tmp/4p8c11259943837.ps tmp/4p8c11259943837.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.963   0.597   1.124