R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(4143,4429,5219,4929,5761,5592,4163,4962,5208,4755,4491,5732,5731,5040,6102,4904,5369,5578,4619,4731,5011,5299,4146,4625,4736,4219,5116,4205,4121,5103,4300,4578,3809,5657,4248,3830,4736,4839,4411,4570,4104,4801,3953,3828,4440,4026,4109,4785,3224,3552,3940,3913,3681,4309,3830,4143,4087,3818,3380,3430,3458,3970,5260,5024,5634,6549,4676)
> 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 -220.568010 4635.093 -271.52484
Feb 1 -231.193654 4694.491  -34.29740
Mar 1  421.180632 4753.889   43.93010
Apr 1  -10.856409 4814.478  125.37852
May 1  161.772721 4875.067  724.16077
Jun 1  688.523091 4938.562  -35.08507
Jul 1 -393.559569 5002.057 -445.49788
Aug 1  -71.387748 5063.479  -30.09107
Sep 1   -6.607645 5124.900   89.70747
Oct 1  184.644741 5160.461 -590.10619
Nov 1 -460.303579 5196.023 -244.71915
Dec 1  -61.644453 5206.639  587.00551
Jan 2 -220.568010 5217.255  734.31284
Feb 2 -231.193654 5218.747   52.44665
Mar 2  421.180632 5220.239  460.58052
Apr 2  -10.856409 5193.704 -278.84733
May 2  161.772721 5167.169   40.05865
Jun 2  688.523091 5106.944 -217.46745
Jul 2 -393.559569 5046.720  -34.16052
Aug 2  -71.387748 4975.499 -173.11078
Sep 2   -6.607645 4904.277  113.33068
Oct 2  184.644741 4837.139  277.21618
Nov 2 -460.303579 4770.001 -163.69762
Dec 2  -61.644453 4712.364  -25.71923
Jan 3 -220.568010 4654.726  301.84184
Feb 3 -231.193654 4610.163 -159.96917
Mar 3  421.180632 4565.599  129.21990
Apr 3  -10.856409 4541.355 -325.49880
May 3  161.772721 4517.111 -557.88367
Jun 3  688.523091 4510.380  -95.90281
Jul 3 -393.559569 4503.648  189.91108
Aug 3  -71.387748 4511.077  138.31040
Sep 3   -6.607645 4518.506 -702.89857
Oct 3  184.644741 4522.145  950.21037
Nov 3 -460.303579 4525.784  182.52001
Dec 3  -61.644453 4507.376 -615.73135
Jan 4 -220.568010 4488.968  467.59996
Feb 4 -231.193654 4450.236  619.95791
Mar 4  421.180632 4411.503 -421.68408
Apr 4  -10.856409 4374.124  206.73247
May 4  161.772721 4336.744 -394.51715
Jun 4  688.523091 4299.133 -186.65622
Jul 4 -393.559569 4261.522   85.03775
Aug 4  -71.387748 4210.522 -311.13393
Sep 4   -6.607645 4159.522  287.08611
Oct 4  184.644741 4110.106 -268.75075
Nov 4 -460.303579 4060.690  508.61309
Dec 4  -61.644453 4025.378  821.26612
Jan 5 -220.568010 3990.066 -545.49816
Feb 5 -231.193654 3966.184 -182.99043
Mar 5  421.180632 3942.302 -423.48263
Apr 5  -10.856409 3912.749   11.10727
May 5  161.772721 3883.196 -363.96899
Jun 5  688.523091 3858.897 -238.42027
Jul 5 -393.559569 3834.598  388.96149
Aug 5  -71.387748 3866.572  347.81610
Sep 5   -6.607645 3898.545  195.06244
Oct 5  184.644741 4014.396 -381.04045
Nov 5 -460.303579 4130.246 -289.94264
Dec 5  -61.644453 4276.156 -784.51114
Jan 6 -220.568010 4422.065 -743.49696
Feb 6 -231.193654 4565.317 -364.12289
Mar 6  421.180632 4708.568  130.25125
Apr 6  -10.856409 4861.631  173.22506
May 6  161.772721 5014.695  457.53270
Jun 6  688.523091 5180.614  679.86340
Jul 6 -393.559569 5346.532 -276.97288
> m$win
  s   t   l 
671  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
68  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/freestat/rcomp/tmp/1688t1291988621.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/freestat/rcomp/tmp/2zi7e1291988621.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/freestat/rcomp/tmp/3zi7e1291988621.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/freestat/rcomp/tmp/4s97z1291988621.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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/561mp1291988621.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/freestat/rcomp/tmp/69jlv1291988621.tab") 
> 
> try(system("convert tmp/1688t1291988621.ps tmp/1688t1291988621.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zi7e1291988621.ps tmp/2zi7e1291988621.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zi7e1291988621.ps tmp/3zi7e1291988621.png",intern=TRUE))
character(0)
> try(system("convert tmp/4s97z1291988621.ps tmp/4s97z1291988621.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.452   0.883   1.614