R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(164,96,73,49,39,59,169,169,210,278,298,245,200,188,90,79,78,91,167,169,289,247,275,203,223,104,107,85,75,99,135,211,335,488,326,346,261,224,141,148,145,223,272,445,560,612,467,404,518,404,300,210,196,186,247,343,464,680,711,610,513,292,273,322,189,257,324,404,677,858,895,664,628,308,324,248,272)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> par8 <- 'FALSE'
> par7 <- '1'
> par6 <- ''
> par5 <- '1'
> par4 <- ''
> par3 <- '0'
> par2 <- 'periodic'
> par1 <- '12'
> #'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   66.236215 168.5128  -70.7490065
Feb 1  -64.997068 167.1907   -6.1936054
Mar 1 -112.944750 165.8686   20.0761933
Apr 1 -141.828596 164.6544   26.1741685
May 1 -167.855322 163.4403   43.4150236
Jun 1 -135.651392 163.0561   31.5953315
Jul 1  -74.953262 162.6718   81.2814396
Aug 1   -7.172677 163.0570   13.1156296
Sep 1  121.774528 163.4423  -75.2168011
Oct 1  224.109489 163.6883 -109.7978161
Nov 1  189.944397 163.9344  -55.8787793
Dec 1  103.338476 167.8989  -26.2373998
Jan 2   66.236215 171.8635  -38.0996798
Feb 2  -64.997068 176.8957   76.1014059
Mar 2 -112.944750 181.9279   21.0168890
Apr 2 -141.828596 183.3203   37.5083279
May 2 -167.855322 184.7127   61.1426467
Jun 2 -135.651392 180.4799   46.1715197
Jul 2  -74.953262 176.2471   65.7061929
Aug 2   -7.172677 171.1339    5.0387762
Sep 2  121.774528 166.0207    1.2047388
Oct 2  224.109489 163.9579 -141.0673445
Nov 2  189.944397 161.8950  -76.8393759
Dec 2  103.338476 163.6630  -64.0015057
Jan 3   66.236215 165.4311   -8.6672950
Feb 3  -64.997068 172.4046   -3.4075025
Mar 3 -112.944750 179.3781   40.5666875
Apr 3 -141.828596 189.4365   37.3920593
May 3 -167.855322 199.4950   43.3603112
Jun 3 -135.651392 206.9906   27.6607929
Jul 3  -74.953262 214.4862   -4.5329253
Aug 3   -7.172677 218.8854   -0.7127197
Sep 3  121.774528 223.2846  -10.0591348
Oct 3  224.109489 228.4979   35.3926044
Nov 3  189.944397 233.7112  -97.6556045
Dec 3  103.338476 243.4723   -0.8107744
Jan 4   66.236215 253.2334  -58.4696037
Feb 4  -64.997068 268.8256   20.1714976
Mar 4 -112.944750 284.4178  -30.4730036
Apr 4 -141.828596 299.9770  -10.1483901
May 4 -167.855322 315.5362   -2.6808966
Jun 4 -135.651392 329.1635   29.4878798
Jul 4  -74.953262 342.7908    4.1624564
Aug 4   -7.172677 354.8603   97.3123542
Sep 4  121.774528 366.9298   71.2956315
Oct 4  224.109489 374.0125   13.8780584
Nov 4  189.944397 381.0951 -104.0394628
Dec 4  103.338476 380.2234  -79.5619250
Jan 5   66.236215 379.3518   72.4119532
Feb 5  -64.997068 375.9147   93.0823628
Mar 5 -112.944750 372.4776   40.4671699
Apr 5 -141.828596 375.5971  -23.7684612
May 5 -167.855322 378.7165  -14.8612123
Jun 5 -135.651392 385.5920  -63.9405743
Jul 5  -74.953262 392.4674  -70.5141361
Aug 5   -7.172677 395.7976  -45.6249566
Sep 5  121.774528 399.1279  -56.9023977
Oct 5  224.109489 403.1965   52.6939840
Nov 5  189.944397 407.2652  113.7904176
Dec 5  103.338476 412.1331   94.5283988
Jan 6   66.236215 417.0011   29.7627204
Feb 6  -64.997068 422.6811  -65.6840579
Mar 6 -112.944750 428.3612  -42.4164386
Apr 6 -141.828596 438.2072   25.6214425
May 6 -167.855322 448.0531  -91.1977965
Jun 6 -135.651392 460.2015  -67.5500748
Jul 6  -74.953262 472.3498  -73.3965530
Aug 6   -7.172677 478.1439  -66.9711919
Sep 6  121.774528 483.9379   71.2875485
Oct 6  224.109489 484.0953  149.7951991
Nov 6  189.944397 484.2527  220.8029016
Dec 6  103.338476 485.2078   75.4537363
Jan 7   66.236215 486.1629   75.6009115
Feb 7  -64.997068 485.5330 -112.5359809
Mar 7 -112.944750 484.9032  -47.9584757
Apr 7 -141.828596 481.6067  -91.7781317
May 7 -167.855322 478.3102  -38.4549078
> m$win
  s   t   l 
771  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
78  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/fisher/rcomp/tmp/1yuwj1355859873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/fisher/rcomp/tmp/2mmtj1355859873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/fisher/rcomp/tmp/3m6p91355859873.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/fisher/rcomp/tmp/4387d1355859873.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/574251355859873.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/fisher/rcomp/tmp/6lxki1355859873.tab") 
> 
> try(system("convert tmp/1yuwj1355859873.ps tmp/1yuwj1355859873.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mmtj1355859873.ps tmp/2mmtj1355859873.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m6p91355859873.ps tmp/3m6p91355859873.png",intern=TRUE))
character(0)
> try(system("convert tmp/4387d1355859873.ps tmp/4387d1355859873.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.454   0.747   3.188