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(267413,267366,264777,258863,254844,254868,277267,285351,286602,283042,276687,277915,277128,277103,275037,270150,267140,264993,287259,291186,292300,288186,281477,282656,280190,280408,276836,275216,274352,271311,289802,290726,292300,278506,269826,265861,269034,264176,255198,253353,246057,235372,258556,260993,254663,250643,243422,247105,248541,245039,237080,237085,225554,226839,247934,248333,246969,245098,246263,255765,264319,268347,273046,273963,267430,271993,292710)
> 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   2198.5257 264021.8  1192.65744
Feb 1   1149.7802 265264.0   952.23364
Mar 1  -2612.1338 266506.2   882.97837
Apr 1  -5266.6050 267716.2 -3586.54759
May 1 -11239.2430 268926.1 -2842.90685
Jun 1 -13534.0738 270070.4 -1668.35725
Jul 1   7196.6001 271214.7 -1144.31243
Aug 1  10507.3209 272312.4  2531.26299
Sep 1   9645.6054 273410.1  3546.27459
Oct 1   3864.7858 274438.5  4738.67235
Nov 1  -2004.2334 275467.0  3224.26973
Dec 1     93.6705 276182.5  1638.80192
Jan 2   2198.5257 276898.1 -1968.61722
Feb 2   1149.7802 277386.3 -1433.04236
Mar 2  -2612.1338 277874.4  -225.29894
Apr 2  -5266.6050 278332.0 -2915.36399
May 2 -11239.2430 278789.5  -410.26233
Jun 2 -13534.0738 279255.6  -728.52827
Jul 2   7196.6001 279721.7   340.70101
Aug 2  10507.3209 280087.7   591.02521
Sep 2   9645.6054 280453.6  2200.78559
Oct 2   3864.7858 280774.1  3547.14385
Nov 2  -2004.2334 281094.5  2386.70173
Dec 2     93.6705 281368.2  1194.14021
Jan 3   2198.5257 281641.8 -3650.37264
Feb 3   1149.7802 281657.0 -2398.73422
Mar 3  -2612.1338 281672.1 -2223.92726
Apr 3  -5266.6050 281216.9  -734.32284
May 3 -11239.2430 280761.8  4829.44828
Jun 3 -13534.0738 279815.1  5030.01081
Jul 3   7196.6001 278868.3  3737.06856
Aug 3  10507.3209 277359.3  2859.40892
Sep 3   9645.6054 275850.2  6804.18547
Oct 3   3864.7858 273683.2   958.05536
Nov 3  -2004.2334 271516.1   314.12487
Dec 3     93.6705 268855.4 -3088.05997
Jan 4   2198.5257 266194.7   640.80386
Feb 4   1149.7802 263479.1  -452.83267
Mar 4  -2612.1338 260763.4 -2953.30066
Apr 4  -5266.6050 258351.2   268.43960
May 4 -11239.2430 255938.9  1357.34657
Jun 4 -13534.0738 254040.4 -5134.30584
Jul 4   7196.6001 252141.9  -782.46303
Aug 4  10507.3209 250578.8   -93.15927
Sep 4   9645.6054 249015.8 -3998.41933
Oct 4   3864.7858 247676.3  -898.03645
Nov 4  -2004.2334 246336.7  -910.45393
Dec 4     93.6705 245254.5  1756.86347
Jan 5   2198.5257 244172.2  2170.22953
Feb 5   1149.7802 243329.8   559.43630
Mar 5  -2612.1338 242487.3 -2795.18839
Apr 5  -5266.6050 242095.6   256.00353
May 5 -11239.2430 241703.9 -4910.63783
Jun 5 -13534.0738 242277.8 -1904.73110
Jul 5   7196.6001 242851.7 -2114.32916
Aug 5  10507.3209 244810.2 -6984.51160
Sep 5   9645.6054 246768.7 -9445.25785
Oct 5   3864.7858 250319.1 -9085.91534
Nov 5  -2004.2334 253869.6 -5602.37320
Dec 5     93.6705 257978.8 -2307.50658
Jan 6   2198.5257 262088.1    32.40870
Feb 6   1149.7802 266312.1   885.14528
Mar 6  -2612.1338 270536.1  5122.05040
Apr 6  -5266.6050 274907.6  4322.04206
May 6 -11239.2430 279279.0  -609.79956
Jun 6 -13534.0738 283743.3  1783.74572
Jul 6   7196.6001 288207.6 -2694.21379
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/16gtn1259963760.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2fwbs1259963760.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/34rrn1259963760.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/4gnpa1259963760.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5j37s1259963760.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6t1rf1259963760.tab") 
> system("convert tmp/16gtn1259963760.ps tmp/16gtn1259963760.png")
> system("convert tmp/2fwbs1259963760.ps tmp/2fwbs1259963760.png")
> system("convert tmp/34rrn1259963760.ps tmp/34rrn1259963760.png")
> system("convert tmp/4gnpa1259963760.ps tmp/4gnpa1259963760.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.971   0.602   1.155