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(12008,9169,8788,8417,8247,8197,8236,8253,7733,8366,8626,8863,10102,8463,9114,8563,8872,8301,8301,8278,7736,7973,8268,9476,11100,8962,9173,8738,8459,8078,8411,8291,7810,8616,8312,9692,9911,8915,9452,9112,8472,8230,8384,8625,8221,8649,8625,10443,10357,8586,8892,8329,8101,7922,8120,7838,7735,8406,8209,9451,10041,9411,10405,8467,8464,8102,7627,7513,7510,8291,8064,9383)
> 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 1824.1809 9101.986 1081.832764
Feb 1  170.5233 9034.899  -36.422055
Mar 1  572.0323 8967.811 -751.843514
Apr 1 -114.6699 8902.165 -370.495097
May 1 -270.2059 8836.519 -319.312816
Jun 1 -558.2061 8770.425  -15.219296
Jul 1 -507.2060 8704.332   38.873933
Aug 1 -546.3469 8646.830  152.516568
Sep 1 -880.8212 8589.329   24.492653
Oct 1 -282.0528 8581.831   66.221915
Nov 1 -308.7844 8574.333  360.451184
Dec 1  901.5568 8585.994 -624.550316
Jan 2 1824.1809 8597.654 -319.834654
Feb 2  170.5233 8605.860 -313.383577
Mar 2  572.0323 8614.067  -72.099139
Apr 2 -114.6699 8620.843   56.827029
May 2 -270.2059 8627.619  514.587061
Jun 2 -558.2061 8652.530  206.676130
Jul 2 -507.2060 8677.441  130.764909
Aug 2 -546.3469 8702.517  121.830241
Sep 2 -880.8212 8727.592 -110.770977
Oct 2 -282.0528 8728.936 -473.883545
Nov 2 -308.7844 8730.281 -153.496105
Dec 2  901.5568 8726.112 -151.668896
Jan 3 1824.1809 8721.944  553.875474
Feb 3  170.5233 8733.725   57.751343
Mar 3  572.0323 8745.507 -144.539427
Apr 3 -114.6699 8759.584   93.086212
May 3 -270.2059 8773.660  -44.454285
Jun 3 -558.2061 8764.129 -127.922491
Jul 3 -507.2060 8754.597  163.609013
Aug 3 -546.3469 8741.136   96.211269
Sep 3 -880.8212 8727.674  -36.853024
Oct 3 -282.0528 8732.894  165.159142
Nov 3 -308.7844 8738.113 -117.328684
Dec 3  901.5568 8749.479   40.963960
Jan 4 1824.1809 8760.845 -674.026234
Feb 4  170.5233 8779.635  -35.158551
Mar 4  572.0323 8798.425   81.542492
Apr 4 -114.6699 8830.836  395.833641
May 4 -270.2059 8863.247 -121.041346
Jun 4 -558.2061 8894.910 -106.704293
Jul 4 -507.2060 8926.574  -35.367529
Aug 4 -546.3469 8921.760  249.586504
Sep 4 -880.8212 8916.947  184.873988
Oct 4 -282.0528 8875.938   55.114910
Nov 4 -308.7844 8834.929   98.855840
Dec 4  901.5568 8788.026  753.417302
Jan 5 1824.1809 8741.123 -208.304073
Feb 5  170.5233 8692.228 -276.751501
Mar 5  572.0323 8643.333 -323.365569
Apr 5 -114.6699 8601.180 -157.509979
May 5 -270.2059 8559.026 -187.820525
Jun 5 -558.2061 8538.066  -57.860201
Jul 5 -507.2060 8517.106  110.099832
Aug 5 -546.3469 8548.854 -164.506991
Sep 5 -880.8212 8580.602   35.219636
Oct 5 -282.0528 8628.236   59.816873
Nov 5 -308.7844 8675.870 -158.085882
Dec 5  901.5568 8692.804 -143.360572
Jan 6 1824.1809 8709.737 -492.918101
Feb 6  170.5233 8695.111  545.365567
Mar 6  572.0323 8680.485 1152.482595
Apr 6 -114.6699 8646.141  -64.471353
May 6 -270.2059 8611.797  122.408562
Jun 6 -558.2061 8578.990   81.216378
Jul 6 -507.2060 8546.182 -411.976097
Aug 6 -546.3469 8506.374 -447.027341
Sep 6 -880.8212 8466.566  -75.745134
Oct 6 -282.0528 8422.369  150.683898
Nov 6 -308.7844 8378.172   -5.387061
Dec 6  901.5568 8332.994  148.448721
> m$win
  s   t   l 
721  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
73  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1b0f21259944874.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/212cg1259944874.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3sqo31259944874.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/4sgu11259944874.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5mci31259944874.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6nh971259944874.tab") 
> 
> system("convert tmp/1b0f21259944874.ps tmp/1b0f21259944874.png")
> system("convert tmp/212cg1259944874.ps tmp/212cg1259944874.png")
> system("convert tmp/3sqo31259944874.ps tmp/3sqo31259944874.png")
> system("convert tmp/4sgu11259944874.ps tmp/4sgu11259944874.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.046   0.643   2.489