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(1.5,1.6,1.8,1.5,1.3,1.6,1.6,1.8,1.8,1.6,1.8,2,1.3,1.1,1,1.2,1.2,1.3,1.3,1.4,1.1,0.9,1,1.1,1.4,1.5,1.8,1.8,1.8,1.7,1.5,1.1,1.3,1.6,1.9,1.9,2,2.2,2.2,2,2.3,2.6,3.2,3.2,3.1,2.8,2.3,1.9,1.9,2,2,1.8,1.6,1.4,0.2,0.3,0.4,0.7,1,1.1)
> 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 -0.086534406 1.6106548 -0.024120382
Feb 1 -0.009412461 1.6127600 -0.003347528
Mar 1  0.087709524 1.6148652  0.097425287
Apr 1 -0.002073935 1.6133480 -0.111274109
May 1 -0.011857380 1.6118309 -0.299973519
Jun 1  0.082084000 1.6047337 -0.086817660
Jul 1 -0.063974279 1.5976364  0.066337859
Aug 1 -0.047333266 1.5863005  0.261032784
Sep 1 -0.050692110 1.5749645  0.275727566
Oct 1 -0.047089857 1.5518888  0.095201048
Nov 1  0.056512304 1.5288131  0.214674621
Dec 1  0.092661780 1.4909068  0.416431418
Jan 2 -0.086534406 1.4530005 -0.066466122
Feb 2 -0.009412461 1.4066387 -0.297226206
Mar 2  0.087709524 1.3602768 -0.447986329
Apr 2 -0.002073935 1.3078462 -0.105772241
May 2 -0.011857380 1.2554155 -0.043558166
Jun 2  0.082084000 1.2247000 -0.006783963
Jul 2 -0.063974279 1.1939844  0.169989900
Aug 2 -0.047333266 1.2103617  0.236971533
Sep 2 -0.050692110 1.2267391 -0.076046978
Oct 2 -0.047089857 1.2697345 -0.322644612
Nov 2  0.056512304 1.3127299 -0.369242155
Dec 2  0.092661780 1.3500069 -0.342668632
Jan 3 -0.086534406 1.3872839  0.099250552
Feb 3 -0.009412461 1.4164379  0.092974538
Mar 3  0.087709524 1.4455920  0.266698486
Apr 3 -0.002073935 1.4855828  0.316491107
May 3 -0.011857380 1.5255737  0.286283715
Jun 3  0.082084000 1.5715446  0.046371363
Jul 3 -0.063974279 1.6175156 -0.053541328
Aug 3 -0.047333266 1.6577251 -0.510391858
Sep 3 -0.050692110 1.6979346 -0.347242532
Oct 3 -0.047089857 1.7450675 -0.097977629
Nov 3  0.056512304 1.7922003  0.051287365
Dec 3  0.092661780 1.8837602 -0.076422024
Jan 4 -0.086534406 1.9753202  0.111214248
Feb 4 -0.009412461 2.1084941  0.100918314
Mar 4  0.087709524 2.2416681 -0.129377660
Apr 4 -0.002073935 2.3467218 -0.344647843
May 4 -0.011857380 2.4517754 -0.139918038
Jun 4  0.082084000 2.4883293  0.029586656
Jul 4 -0.063974279 2.5248833  0.739091010
Aug 4 -0.047333266 2.5130783  0.734255009
Sep 4 -0.050692110 2.5012732  0.649418865
Oct 4 -0.047089857 2.4437339  0.403355986
Nov 4  0.056512304 2.3861945 -0.142706800
Dec 4  0.092661780 2.2444254 -0.437087206
Jan 5 -0.086534406 2.1026564 -0.116121949
Feb 5 -0.009412461 1.8991186  0.110293877
Mar 5  0.087709524 1.6955808  0.216709665
Apr 5 -0.002073935 1.5398136  0.262260369
May 5 -0.011857380 1.3840463  0.227811060
Jun 5  0.082084000 1.2473424  0.070573562
Jul 5 -0.063974279 1.1106386 -0.846664275
Aug 5 -0.047333266 0.9723002 -0.624966947
Sep 5 -0.050692110 0.8339619 -0.383269764
Oct 5 -0.047089857 0.6973432  0.049746637
Nov 5  0.056512304 0.5607246  0.382763129
Dec 5  0.092661780 0.4291964  0.578141827
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/10os61293388362.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2tyar1293388362.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/html/rcomp/tmp/3tyar1293388362.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/html/rcomp/tmp/4l79c1293388362.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/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5iy731293388362.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/63z5r1293388362.tab") 
> 
> try(system("convert tmp/10os61293388362.ps tmp/10os61293388362.png",intern=TRUE))
character(0)
> try(system("convert tmp/2tyar1293388362.ps tmp/2tyar1293388362.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tyar1293388362.ps tmp/3tyar1293388362.png",intern=TRUE))
character(0)
> try(system("convert tmp/4l79c1293388362.ps tmp/4l79c1293388362.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.956   0.607   2.144