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(6802.96,7132.68,7073.29,7264.5,7105.33,7218.71,7225.72,7354.25,7745.46,8070.26,8366.33,8667.51,8854.34,9218.1,9332.9,9358.31,9248.66,9401.2,9652.04,9957.38,10110.63,10169.26,10343.78,10750.21,11337.5,11786.96,12083.04,12007.74,11745.93,11051.51,11445.9,11924.88,12247.63,12690.91,12910.7,13202.12,13654.67,13862.82,13523.93,14211.17,14510.35,14289.23,14111.82,13086.59,13351.54,13747.69,12855.61,12926.93,12121.95,11731.65,11639.51,12163.78,12029.53,11234.18,9852.13,9709.04,9332.75,7108.6,6691.49,6143.05)
> 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   95.20134  6462.720  245.038196
Feb 1  221.71887  6645.232  265.729103
Mar 1  140.17029  6827.744  105.376130
Apr 1  392.52092  7014.148 -142.168499
May 1  301.16570  7200.552 -396.387274
Jun 1   10.98714  7386.888 -179.165312
Jul 1 -171.64094  7573.225 -175.863834
Aug 1 -210.71738  7757.304 -192.336710
Sep 1  -47.52572  7941.383 -148.397687
Oct 1 -225.88816  8133.231  162.916853
Nov 1 -327.75528  8325.079  369.006069
Dec 1 -178.23696  8513.308  332.438473
Jan 2   95.20134  8701.538   57.600899
Feb 2  221.71887  8885.233  111.148050
Mar 2  140.17029  9068.928  123.801322
Apr 2  392.52092  9246.288 -280.498900
May 2  301.16570  9423.648 -476.153268
Jun 2   10.98714  9610.067 -219.854475
Jul 2 -171.64094  9796.487   27.193834
Aug 2 -210.71738 10014.459  153.638818
Sep 2  -47.52572 10232.430  -74.274298
Oct 2 -225.88816 10450.552  -55.403862
Nov 2 -327.75528 10668.674    2.861250
Dec 2 -178.23696 10848.788   79.658922
Jan 3   95.20134 11028.902  213.396617
Feb 3  221.71887 11188.424  376.817367
Mar 3  140.17029 11347.945  594.924236
Apr 3  392.52092 11525.259   89.959692
May 3  301.16570 11702.573 -257.808998
Jun 3   10.98714 11890.674 -850.151470
Jul 3 -171.64094 12078.775 -461.234425
Aug 3 -210.71738 12266.469 -130.871509
Sep 3  -47.52572 12454.162 -159.006693
Oct 3 -225.88816 12662.605  254.193619
Nov 3 -327.75528 12871.047  367.408608
Dec 3 -178.23696 13086.360  293.997244
Jan 4   95.20134 13301.673  257.795902
Feb 4  221.71887 13447.753  193.348112
Mar 4  140.17029 13593.833 -210.073557
Apr 4  392.52092 13649.875  168.773968
May 4  301.16570 13705.917  503.267346
Jun 4   10.98714 13666.046  612.196459
Jul 4 -171.64094 13626.176  657.285087
Aug 4 -210.71738 13486.931 -189.624073
Sep 4  -47.52572 13347.687   51.378666
Oct 4 -225.88816 13138.702  834.876124
Nov 4 -327.75528 12929.717  253.648258
Dec 4 -178.23696 12663.389  441.777998
Jan 5   95.20134 12397.061 -370.312241
Feb 5  221.71887 12063.183 -553.251634
Mar 5  140.17029 11729.305 -229.964906
Apr 5  392.52092 11236.240  535.019476
May 5  301.16570 10743.175  985.189712
Jun 5   10.98714 10233.929  989.263795
Jul 5 -171.64094  9724.684  299.087394
Aug 5 -210.71738  9210.031  709.726144
Sep 5  -47.52572  8695.379  684.896795
Oct 5 -225.88816  8165.505 -831.016728
Nov 5 -327.75528  7635.631 -616.385575
Dec 5 -178.23696  7089.924 -768.637211
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/162oi1259956255.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/20av61259956255.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/33oum1259956255.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/4yek01259956255.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5q7mb1259956255.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/64uoo1259956255.tab") 
> system("convert tmp/162oi1259956255.ps tmp/162oi1259956255.png")
> system("convert tmp/20av61259956255.ps tmp/20av61259956255.png")
> system("convert tmp/33oum1259956255.ps tmp/33oum1259956255.png")
> system("convert tmp/4yek01259956255.ps tmp/4yek01259956255.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.964   0.605   1.125