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(9700,9081,9084,9743,8587,9731,9563,9998,9437,10038,9918,9252,9737,9035,9133,9487,8700,9627,8947,9283,8829,9947,9628,9318,9605,8640,9214,9567,8547,9185,9470,9123,9278,10170,9434,9655,9429,8739,9552,9687,9019,9672,9206,9069,9788,10312,10105,9863,9656,9295,9946,9701,9049,10190,9706,9765,9893,9994,10433,10073,10112,9266,9820,10097,9115,10411,9678,10408,10153,10368,10581,10597,10680,9738,9556)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '6'
> main = 'Seasonal Decomposition by Loess'
> par8 <- 'FALSE'
> par7 <- '1'
> par6 <- ''
> par5 <- '1'
> par4 <- ''
> par3 <- '0'
> par2 <- 'periodic'
> par1 <- '6'
> #'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
Time Series:
Start = c(1, 1) 
End = c(13, 3) 
Frequency = 6 
            seasonal     trend   remainder
 1.000000   52.16881  9338.419  309.412517
 1.166667 -270.65156  9349.994    1.657685
 1.333333 -109.46836  9361.569 -168.100720
 1.500000  327.46343  9390.105   25.431765
 1.666667 -182.01005  9418.641 -649.630487
 1.833333  182.49792  9488.866   59.635667
 2.000000   52.16881  9559.092  -48.261099
 2.166667 -270.65156  9638.008  630.643257
 2.333333 -109.46836  9716.924 -170.455962
 2.500000  327.46343  9679.553   30.983630
 2.666667 -182.01005  9642.182  457.828485
 2.833333  182.49792  9547.482 -477.979842
 3.000000   52.16881  9452.782  232.048912
 3.166667 -270.65156  9358.090  -52.438299
 3.333333 -109.46836  9263.397  -20.929084
 3.500000  327.46343  9224.189  -64.652114
 3.666667 -182.01005  9184.980 -302.969881
 3.833333  182.49792  9197.847  246.655054
 4.000000   52.16881  9210.714 -315.882931
 4.166667 -270.65156  9277.396  276.255423
 4.333333 -109.46836  9344.078 -405.609798
 4.500000  327.46343  9361.985  257.551144
 4.666667 -182.01005  9379.893  430.117349
 4.833333  182.49792  9354.294 -218.792188
 5.000000   52.16881  9328.696  224.135354
 5.166667 -270.65156  9242.984 -332.332520
 5.333333 -109.46836  9157.272  166.196032
 5.500000  327.46343  9150.249   89.287089
 5.666667 -182.01005  9143.227 -414.216591
 5.833333  182.49792  9203.828 -201.326143
 6.000000   52.16881  9264.430  153.401385
 6.166667 -270.65156  9363.979   29.672399
 6.333333 -109.46836  9463.529  -76.060161
 6.500000  327.46343  9477.613  364.923452
 6.666667 -182.01005  9491.698  124.312329
 6.833333  182.49792  9465.480    7.022493
 7.000000   52.16881  9439.261  -62.430262
 7.166667 -270.65156  9396.594 -386.942769
 7.333333 -109.46836  9353.927  307.541149
 7.500000  327.46343  9350.996    8.540948
 7.666667 -182.01005  9348.064 -147.053990
 7.833333  182.49792  9410.544   78.958552
 8.000000   52.16881  9473.023 -319.191826
 8.166667 -270.65156  9584.521 -244.869303
 8.333333 -109.46836  9696.019  201.449646
 8.500000  327.46343  9755.731  228.805999
 8.666667 -182.01005  9815.442  471.567616
 8.833333  182.49792  9798.728 -118.225795
 9.000000   52.16881  9782.013 -178.182126
 9.166667 -270.65156  9710.242 -144.589942
 9.333333 -109.46836  9638.470  416.998668
 9.500000  327.46343  9659.484 -285.947701
 9.666667 -182.01005  9680.499 -449.488808
 9.833333  182.49792  9726.469  281.033189
10.000000   52.16881  9772.439 -118.607733
10.166667 -270.65156  9868.999  166.652137
10.333333 -109.46836  9965.560   36.908433
10.500000  327.46343  9980.979 -314.442688
10.666667 -182.01005  9996.399  618.611455
10.833333  182.49792  9963.126  -72.624126
11.000000   52.16881  9929.854  129.977373
11.166667 -270.65156  9862.148 -325.496921
11.333333 -109.46836  9794.443  135.025211
11.500000  327.46343  9817.033  -47.496779
11.666667 -182.01005  9839.624 -542.613506
11.833333  182.49792  9931.827  296.675386
12.000000   52.16881 10024.030 -398.198641
12.166667 -270.65156 10148.879  529.772407
12.333333 -109.46836 10273.728  -11.260119
12.500000  327.46343 10299.515 -258.978182
12.666667 -182.01005 10325.301  437.709017
12.833333  182.49792 10262.037  152.464890
13.000000   52.16881 10198.773  429.057843
13.166667 -270.65156 10122.129 -113.477378
13.333333 -109.46836 10045.485 -380.016174
> m$win
  s   t   l 
751  11   7 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
76  2  1 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1urve1352732338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2kiny1352732338.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/38ydn1352732338.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/48tt61352732338.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5u3hb1352732338.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6wcl01352732338.tab") 
> 
> try(system("convert tmp/1urve1352732338.ps tmp/1urve1352732338.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kiny1352732338.ps tmp/2kiny1352732338.png",intern=TRUE))
character(0)
> try(system("convert tmp/38ydn1352732338.ps tmp/38ydn1352732338.png",intern=TRUE))
character(0)
> try(system("convert tmp/48tt61352732338.ps tmp/48tt61352732338.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.394   0.366   2.760