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(12008,9169,8788,8417,8247,8197,8236,8253,7733,8366,8626,8863,10102,8463,9114,8563,8872,8301,8301,8278,7736,7973,8268,9476,11100,8962,9173,8738,8459,8078,8411,8291,7810,8616,8312,9692,9911,8915,9452,9112,8472,8230,8384,8625,8221,8649,8625,10443,10357,8586,8892,8329,8101,7922,8120,7838,7735,8406,8209,9451,10041,9411,10405,8467,8464,8102,7627,7513,7510,8291,8064,9383,9706,8579,9474,8318,8213,8059,9111,7708,7680,8014,8007,8718,9486,9113,9025,8476,7952,7759,7835,7600,7651,8319,8812,8630)
> 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 1665.30645 9099.684 1243.010050
Feb 1  236.65795 9032.127  -99.785295
Mar 1  637.75969 8964.571 -814.330865
Apr 1  -93.17707 8898.996 -388.819225
May 1 -291.23873 8833.421 -295.182688
Jun 1 -549.31981 8767.583  -21.262699
Jul 1 -368.77585 8701.744  -96.967759
Aug 1 -601.95250 8644.923  210.029442
Sep 1 -849.00424 8588.103   -6.098281
Oct 1 -276.97438 8583.250   59.724653
Nov 1 -238.56984 8578.397  286.172896
Dec 1  729.28836 8589.844 -456.132675
Jan 2 1665.30645 8601.292 -164.598146
Feb 2  236.65795 8608.502 -382.159687
Mar 2  637.75969 8615.712 -139.471454
Apr 2  -93.17707 8619.488   36.689559
May 2 -291.23873 8623.263  539.975468
Jun 2 -549.31981 8648.144  202.175589
Jul 2 -368.77585 8673.025   -3.249337
Aug 2 -601.95250 8700.078  179.874432
Sep 2 -849.00424 8727.131 -142.126722
Oct 2 -276.97438 8730.738 -480.763211
Nov 2 -238.56984 8734.344 -227.774390
Dec 2  729.28836 8729.963   16.748743
Jan 3 1665.30645 8725.582  709.111977
Feb 3  236.65795 8736.367  -11.024773
Mar 3  637.75969 8747.152 -211.911748
Apr 3  -93.17707 8758.228   72.948739
May 3 -291.23873 8769.305  -19.065878
Jun 3 -549.31981 8759.743 -132.423028
Jul 3 -368.77585 8750.181   29.594773
Aug 3 -601.95250 8738.697  154.255467
Sep 3 -849.00424 8727.213  -68.208763
Oct 3 -276.97438 8734.695  158.279479
Nov 3 -238.56984 8742.177 -191.606970
Dec 3  729.28836 8753.330  209.381596
Jan 4 1665.30645 8764.483 -518.789738
Feb 4  236.65795 8782.277 -103.934674
Mar 4  637.75969 8800.070   14.170165
Apr 4  -93.17707 8829.481  375.696165
May 4 -291.23873 8858.892  -95.652938
Jun 4 -549.31981 8890.525 -111.204826
Jul 4 -368.77585 8922.158 -169.381763
Aug 4 -601.95250 8919.322  307.630708
Sep 4 -849.00424 8916.486  153.518255
Oct 4 -276.97438 8877.739   48.235250
Nov 4 -238.56984 8838.992   24.577554
Dec 4  729.28836 8791.877  921.834934
Jan 5 1665.30645 8744.761  -53.067585
Feb 5  236.65795 8694.870 -345.527631
Mar 5  637.75969 8644.978 -390.737902
Apr 5  -93.17707 8599.825 -177.647457
May 5 -291.23873 8554.671 -162.432115
Jun 5 -549.31981 8533.681  -62.360731
Jul 5 -368.77585 8512.690  -23.914395
Aug 5 -601.95250 8546.415 -106.462781
Sep 5 -849.00424 8580.140    3.863909
Oct 5 -276.97438 8630.037   52.937215
Nov 5 -238.56984 8679.934 -232.364169
Dec 5  729.28836 8696.655   25.057054
Jan 6 1665.30645 8713.375 -337.681622
Feb 6  236.65795 8697.753  476.589427
Mar 6  637.75969 8682.130 1085.110251
Apr 6  -93.17707 8657.257  -97.079918
May 6 -291.23873 8632.384  122.854809
Jun 6 -549.31981 8594.258   57.061571
Jul 6 -368.77585 8556.133 -560.356716
Aug 6 -601.95250 8507.374 -392.421368
Sep 6 -849.00424 8458.615  -99.610944
Oct 6 -276.97438 8433.254  134.720735
Nov 6 -238.56984 8407.892 -105.322278
Dec 6  729.28836 8432.760  220.951639
Jan 7 1665.30645 8457.628 -416.934344
Feb 7  236.65795 8491.378 -149.035934
Mar 7  637.75969 8525.128  311.112251
Apr 7  -93.17707 8530.968 -119.790436
May 7 -291.23873 8536.807  -32.568227
Jun 7 -549.31981 8519.361   88.959090
Jul 7 -368.77585 8501.914  977.861359
Aug 7 -601.95250 8485.135 -175.182420
Sep 7 -849.00424 8468.355   60.648878
Oct 7 -276.97438 8445.576 -154.601503
Nov 7 -238.56984 8422.796 -177.226576
Dec 7  729.28836 8390.650 -401.938420
Jan 8 1665.30645 8358.504 -537.810165
Feb 8  236.65795 8339.368  536.974530
Mar 8  637.75969 8320.231   67.009000
Apr 8  -93.17707 8341.268  227.908841
May 8 -291.23873 8362.305 -119.066422
Jun 8 -549.31981 8376.770  -68.450124
Jul 8 -368.77585 8391.235 -187.458875
Aug 8 -601.95250 8403.534 -201.581116
Sep 8 -849.00424 8415.833   84.171719
Oct 8 -276.97438 8428.557  167.417485
Nov 8 -238.56984 8441.281  609.288560
Dec 8  729.28836 8454.683 -553.971597
> m$win
  s   t   l 
961  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
97  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1igrv1353681532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/27day1353681532.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3veg71353681532.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/4p7cw1353681532.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5vy8c1353681532.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6mkj91353681533.tab") 
> 
> try(system("convert tmp/1igrv1353681532.ps tmp/1igrv1353681532.png",intern=TRUE))
character(0)
> try(system("convert tmp/27day1353681532.ps tmp/27day1353681532.png",intern=TRUE))
character(0)
> try(system("convert tmp/3veg71353681532.ps tmp/3veg71353681532.png",intern=TRUE))
character(0)
> try(system("convert tmp/4p7cw1353681532.ps tmp/4p7cw1353681532.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.578   0.388   2.947