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(1.4,1,-0.8,-2.9,-0.7,-0.7,1.5,3,3.2,3.1,3.9,1,1.3,0.8,1.2,2.9,3.9,4.5,4.5,3.3,2,1.5,1,2.1,3,4,5.1,4.5,4.2,3.3,2.7,1.8,1.4,0.5,-0.4,0.8,0.7,1.9,2,1.1,0.9,0.4,0.7,2.1,2.8,3.9,3.5,2,2,1.5,2.5,3.1,2.7,2.8,2.5,3,3.2,2.8,2.4,2,1.8,1.1,-1.5,-3.7)
> 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 -0.006242259 -0.31979404  1.726036299
Feb 1  0.005912555 -0.09246991  1.086557351
Mar 1 -0.298598181  0.13485423 -0.636256047
Apr 1 -0.855413904  0.35603444 -2.400620531
May 1  0.108328758  0.57721464 -1.385543400
Jun 1 -0.043761954  0.77570824 -1.431946290
Jul 1  0.264147032  0.97420185  0.261651122
Aug 1  0.549649087  1.17086990  1.279481011
Sep 1  0.455151509  1.36753796  1.377310534
Oct 1  0.294992176  1.65955532  1.145452508
Nov 1  0.014832487  1.95157268  1.933594837
Dec 1 -0.488996896  2.21552170 -0.726524805
Jan 2 -0.006242259  2.47947073 -1.173228468
Feb 2  0.005912555  2.57285700 -1.778769559
Mar 2 -0.298598181  2.66624328 -1.167645100
Apr 2 -0.855413904  2.63489699  1.120516912
May 2  0.108328758  2.60355070  1.188120539
Jun 2 -0.043761954  2.62024707  1.923514882
Jul 2  0.264147032  2.63694344  1.598909527
Aug 2  0.549649087  2.75539698 -0.005046071
Sep 2  0.455151509  2.87385053 -1.329002035
Oct 2  0.294992176  2.97498361 -1.769975787
Nov 2  0.014832487  3.07611670 -2.090949184
Dec 2 -0.488996896  3.10557916 -0.516582267
Jan 3 -0.006242259  3.13504163 -0.128799370
Feb 3  0.005912555  3.11697373  0.877113710
Mar 3 -0.298598181  3.09890584  2.299692340
Apr 3 -0.855413904  3.00094753  2.354466371
May 3  0.108328758  2.90298923  1.188682016
Jun 3 -0.043761954  2.68447137  0.659290587
Jul 3  0.264147032  2.46595351 -0.030100541
Aug 3  0.549649087  2.18916666 -0.938815747
Sep 3  0.455151509  1.91237981 -0.967531321
Oct 3  0.294992176  1.66683209 -1.461824267
Nov 3  0.014832487  1.42128437 -1.836116857
Dec 3 -0.488996896  1.27745559  0.011541309
Jan 4 -0.006242259  1.13362680 -0.427384545
Feb 4  0.005912555  1.15090128  0.743186160
Mar 4 -0.298598181  1.16817576  1.130422417
Apr 4 -0.855413904  1.33058739  0.624826513
May 4  0.108328758  1.49299902 -0.701327777
Jun 4 -0.043761954  1.64549789 -1.201735937
Jul 4  0.264147032  1.79799676 -1.362143796
Aug 4  0.549649087  1.89318306 -0.342832148
Sep 4  0.455151509  1.98836936  0.356479133
Oct 4  0.294992176  2.12000190  1.485005921
Nov 4  0.014832487  2.25163445  1.233533065
Dec 4 -0.488996896  2.39821083  0.090786063
Jan 5 -0.006242259  2.54478722 -0.538544959
Feb 5  0.005912555  2.60091161 -1.106824166
Mar 5 -0.298598181  2.65703600  0.141562178
Apr 5 -0.855413904  2.63733656  1.318077340
May 5  0.108328758  2.61763712 -0.025965883
Jun 5 -0.043761954  2.58396157  0.259800382
Jul 5  0.264147032  2.55028602 -0.314433051
Aug 5  0.549649087  2.29784668  0.152504230
Sep 5  0.455151509  2.04540735  0.699441144
Oct 5  0.294992176  1.72427445  0.780733374
Nov 5  0.014832487  1.40314155  0.982025961
Dec 5 -0.488996896  1.07008661  1.418910282
Jan 6 -0.006242259  0.73703168  1.069210583
Feb 6  0.005912555  0.38425390  0.709833542
Mar 6 -0.298598181  0.03147613 -1.232877948
Apr 6 -0.855413904 -0.34566854 -2.498917559
> m$win
  s   t   l 
641  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
65  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/109r41259961556.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2vo0w1259961556.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3bjem1259961556.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/47kfd1259961556.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5rkhq1259961556.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/651qw1259961556.tab") 
> system("convert tmp/109r41259961556.ps tmp/109r41259961556.png")
> system("convert tmp/2vo0w1259961556.ps tmp/2vo0w1259961556.png")
> system("convert tmp/3bjem1259961556.ps tmp/3bjem1259961556.png")
> system("convert tmp/47kfd1259961556.ps tmp/47kfd1259961556.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.965   0.623   1.148