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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(15579,16348,15928,16171,15937,15713,15594,15683,16438,17032,17696,17745,19394,20148,20108,18584,18441,18391,19178,18079,18483,19644,19195,19650,20830,23595,22937,21814,21928,21777,21383,21467,22052,22680,24320,24977,25204,25739,26434,27525,30695,32436,30160,30236,31293,31077,32226,33865,32810,32242,32700,32819,33947,34148,35261,39506,41591,39148,41216,40225,41126,42362,40740,40256,39804,41002,41702,42254,43605,43271)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> 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  160.45195 15261.10   157.44352
Feb 1  701.33503 15464.81   181.85091
Mar 1   62.55186 15668.52   196.92455
Apr 1 -561.98896 15889.64   843.34855
May 1 -309.69542 16110.76   135.93820
Jun 1 -181.88617 16348.77  -453.88543
Jul 1 -538.07768 16586.79  -454.70828
Aug 1 -227.12593 16829.16  -919.02968
Sep 1  465.49237 17071.53 -1099.01762
Oct 1  -25.49122 17335.71  -278.22047
Nov 1  284.60683 17599.90  -188.50496
Dec 1  169.82852 17878.90  -303.73016
Jan 2  160.45195 18157.91  1075.64290
Feb 2  701.33503 18385.49  1061.17403
Mar 2   62.55186 18613.08  1432.37141
Apr 2 -561.98896 18764.21   381.77838
May 2 -309.69542 18915.34  -164.64902
Jun 2 -181.88617 19028.67  -455.78388
Jul 2 -538.07768 19142.00   574.08203
Aug 2 -227.12593 19330.04 -1023.91672
Sep 2  465.49237 19518.09 -1500.58201
Oct 2  -25.49122 19803.75  -134.25458
Nov 2  284.60683 20089.40 -1179.00879
Dec 2  169.82852 20407.18  -927.01078
Jan 3  160.45195 20724.96   -55.41450
Feb 3  701.33503 21022.02  1871.64848
Mar 3   62.55186 21319.07  1555.37770
Apr 3 -561.98896 21620.58   755.40696
May 3 -309.69542 21922.09   315.60185
Jun 3 -181.88617 22219.93  -261.04479
Jul 3 -538.07768 22517.77  -596.69067
Aug 3 -227.12593 22827.60 -1133.47628
Sep 3  465.49237 23137.44 -1550.92844
Oct 3  -25.49122 23640.25  -934.75848
Nov 3  284.60683 24143.06  -107.67015
Dec 3  169.82852 24896.20   -89.03052
Jan 4  160.45195 25649.34  -605.79262
Feb 4  701.33503 26463.35 -1425.68388
Mar 4   62.55186 27277.36  -905.90889
Apr 4 -561.98896 28029.22    57.77215
May 4 -309.69542 28781.08  2223.61883
Jun 4 -181.88617 29456.79  3161.09519
Jul 4 -538.07768 30132.51   565.57231
Aug 4 -227.12593 30668.33  -205.19941
Sep 4  465.49237 31204.15  -376.63767
Oct 4  -25.49122 31565.40  -462.90918
Nov 4  284.60683 31926.66    14.73768
Dec 4  169.82852 32273.96  1421.21045
Jan 5  160.45195 32621.27    28.28148
Feb 5  701.33503 33198.68 -1658.01120
Mar 5   62.55186 33776.09 -1138.63764
Apr 5 -561.98896 34499.38 -1118.39521
May 5 -309.69542 35222.68  -965.98715
Jun 5 -181.88617 35979.04 -1649.15767
Jul 5 -538.07768 36735.41  -936.32742
Aug 5 -227.12593 37491.94  2241.18972
Sep 5  465.49237 38248.47  2877.04030
Oct 5  -25.49122 38888.65   284.84444
Nov 5  284.60683 39528.83  1402.56694
Dec 5  169.82852 39978.53    76.64031
Jan 6  160.45195 40428.24   537.31194
Feb 6  701.33503 40707.82   952.84533
Mar 6   62.55186 40987.40  -309.95504
Apr 6 -561.98896 41266.34  -448.34805
May 6 -309.69542 41545.27 -1431.57541
Jun 6 -181.88617 41812.82  -628.92995
Jul 6 -538.07768 42080.36   159.71628
Aug 6 -227.12593 42348.30   132.82665
Sep 6  465.49237 42616.24   523.27047
Oct 6  -25.49122 42889.99   406.50512
> m$win
  s   t   l 
701  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
71  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1sppa1353682306.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/wessaorg/rcomp/tmp/28lty1353682306.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$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3blev1353682306.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$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$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4xy3z1353682306.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$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$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Component',header=TRUE)
> a<-table.element(a,'Window',header=TRUE)
> a<-table.element(a,'Degree',header=TRUE)
> a<-table.element(a,'Jump',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,m$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/wessaorg/rcomp/tmp/57jme1353682306.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/wessaorg/rcomp/tmp/6ygnx1353682306.tab") 
> 
> try(system("convert tmp/1sppa1353682306.ps tmp/1sppa1353682306.png",intern=TRUE))
character(0)
> try(system("convert tmp/28lty1353682306.ps tmp/28lty1353682306.png",intern=TRUE))
character(0)
> try(system("convert tmp/3blev1353682306.ps tmp/3blev1353682306.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xy3z1353682306.ps tmp/4xy3z1353682306.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.734   0.439   3.154