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(325412,326011,328282,317480,317539,313737,312276,309391,302950,300316,304035,333476,337698,335932,323931,313927,314485,313218,309664,302963,298989,298423,310631,329765,335083,327616,309119,295916,291413,291542,284678,276475,272566,264981,263290,296806,303598,286994,276427,266424,267153,268381,262522,255542,253158,243803,250741,280445,285257,270976,261076,255603,260376,263903,264291,263276,262572,256167,264221,293860,300713,287224)
> 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  22528.704 313823.0 -10939.66142
Feb 1  14011.088 314265.7  -2265.82480
Mar 1   6214.732 314708.5   7358.75236
Apr 1  -3058.852 315120.5   5418.35596
May 1  -2112.238 315532.5   4118.75998
Jun 1  -1686.630 315952.3   -528.66847
Jul 1  -4694.026 316372.1    597.90565
Aug 1  -9363.873 316732.0   2022.90533
Sep 1 -12359.317 317091.8  -1782.49765
Oct 1 -17076.617 317024.1    368.56444
Nov 1 -10639.316 316956.3  -2281.97338
Dec 1  18236.349 316804.2  -1564.56406
Jan 2  22528.704 316652.1  -1482.84462
Feb 2  14011.088 316412.5   5508.44570
Mar 2   6214.732 316172.8   1543.47656
Apr 2  -3058.852 316014.2    971.60878
May 2  -2112.238 315855.7    741.54141
Jun 2  -1686.630 315635.4   -730.79606
Jul 2  -4694.026 315415.2  -1057.13094
Aug 2  -9363.873 314773.3  -2446.41623
Sep 2 -12359.317 314131.4  -2783.10417
Oct 2 -17076.617 312860.1   2639.48137
Nov 2 -10639.316 311588.8   9681.46699
Dec 2  18236.349 309741.0   1787.61557
Jan 3  22528.704 307893.2   4661.07428
Feb 3  14011.088 305481.0   8123.92822
Mar 3   6214.732 303068.7   -164.47730
Apr 3  -3058.852 300069.0  -1094.18781
May 3  -2112.238 297069.3  -3544.09789
Jun 3  -1686.630 293923.9   -695.25333
Jul 3  -4694.026 290778.4  -1406.40619
Aug 3  -9363.873 287932.3  -2093.42693
Sep 3 -12359.317 285086.2   -160.85032
Oct 3 -17076.617 282692.4   -634.75685
Nov 3 -10639.316 280298.6  -6369.26330
Dec 3  18236.349 278302.5    267.18037
Jan 4  22528.704 276306.4   4762.93417
Feb 4  14011.088 274599.6  -1616.69331
Mar 4   6214.732 272892.8  -2680.58025
Apr 4  -3058.852 271366.3  -1883.47336
May 4  -2112.238 269839.8   -574.56606
Jun 4  -1686.630 268470.3   1597.34962
Jul 4  -4694.026 267100.8    115.26787
Aug 4  -9363.873 265828.2   -922.35458
Sep 4 -12359.317 264555.7    961.62032
Oct 4 -17076.617 263597.4  -2717.74260
Nov 4 -10639.316 262639.0  -1258.70542
Dec 4  18236.349 262258.6    -49.94076
Jan 5  22528.704 261878.2    850.13401
Feb 5  14011.088 262306.2  -5341.25516
Mar 5   6214.732 262734.2  -7872.90379
Apr 5  -3058.852 263765.0  -5103.15804
May 5  -2112.238 264795.8  -2307.61188
Jun 5  -1686.630 266307.1   -717.51395
Jul 5  -4694.026 267818.4   1166.58656
Aug 5  -9363.873 269304.3   3335.61248
Sep 5 -12359.317 270790.1   4141.23574
Oct 5 -17076.617 272327.0    916.58709
Nov 5 -10639.316 273864.0    996.33853
Dec 5  18236.349 275410.7    212.92440
Jan 6  22528.704 276957.5   1226.82039
Feb 6  14011.088 278485.5  -5272.62293
> m$win
  s   t   l 
621  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
63  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1t91y1259689607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2ics11259689607.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3fbh81259689607.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/4ls731259689607.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5upy41259689607.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6sbra1259689607.tab") 
> system("convert tmp/1t91y1259689607.ps tmp/1t91y1259689607.png")
> system("convert tmp/2ics11259689607.ps tmp/2ics11259689607.png")
> system("convert tmp/3fbh81259689607.ps tmp/3fbh81259689607.png")
> system("convert tmp/4ls731259689607.ps tmp/4ls731259689607.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.963   0.609   1.368