R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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(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'
> #'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 1301.08166 8730.648 -120.7292759
Feb 1  325.94771 8758.336 -169.2840380
Mar 1  859.01425 8786.025 -193.0392852
Apr 1  -45.63989 8808.325  349.3152315
May 1 -341.09326 8830.624  -17.5310107
Jun 1 -559.06374 8847.235  -58.1714040
Jul 1 -350.03422 8863.846 -129.8118008
Aug 1 -708.30090 8874.692  458.6089093
Sep 1 -805.36725 8885.538  140.8292935
Oct 1 -227.68575 8863.954   12.7318986
Nov 1 -218.80451 8842.370    1.4347613
Dec 1  769.94558 8793.098  879.9564451
Jan 2 1301.08166 8743.826  312.0921382
Feb 2  325.94771 8694.198 -434.1453296
Mar 2  859.01425 8644.569 -611.5832824
Apr 2  -45.63989 8598.121 -223.4815496
May 2 -341.09326 8551.674 -109.5805756
Jun 2 -559.06374 8531.595  -50.5309407
Jul 2 -350.03422 8511.516  -41.4813093
Aug 2 -708.30090 8546.847   -0.5463287
Sep 2 -805.36725 8582.179  -41.8116741
Oct 2 -227.68575 8632.745    0.9405546
Nov 2 -218.80451 8683.311 -255.5069591
Dec 2  769.94558 8697.876  -16.8214338
Jan 3 1301.08166 8712.440   27.4781010
Feb 3  325.94771 8697.081  387.9717291
Mar 3  859.01425 8681.721  864.2648722
Apr 3  -45.63989 8655.554 -142.9140093
May 3 -341.09326 8629.387  175.7063503
Jun 3 -559.06374 8592.172   68.8913624
Jul 3 -350.03422 8554.958 -577.9236290
Aug 3 -708.30090 8507.806 -286.5049151
Sep 3 -805.36725 8460.654 -145.2865272
Oct 3 -227.68575 8435.962   82.7240736
Nov 3 -218.80451 8411.270 -128.4650679
Dec 3  769.94558 8433.981  179.0731500
Jan 4 1301.08166 8456.693  -51.7746226
Feb 4  325.94771 8490.706 -237.6536326
Mar 4  859.01425 8524.719   90.2668724
Apr 4  -45.63989 8529.264 -165.6245263
May 4 -341.09326 8533.810   20.2833161
Jun 4 -559.06374 8517.275  100.7888828
Jul 4 -350.03422 8500.740  960.2944459
Aug 4 -708.30090 8485.567  -69.2659675
Sep 4 -805.36725 8470.394   14.9732931
Oct 4 -227.68575 8448.284 -206.5981665
Nov 4 -218.80451 8426.174 -200.3693686
Dec 4  769.94558 8391.871 -443.8169133
Jan 5 1301.08166 8357.569 -172.6504487
Feb 5  325.94771 8338.695  448.3568256
Mar 5  859.01425 8319.822 -153.8363851
Apr 5  -45.63989 8338.453  183.1867926
May 5 -341.09326 8357.084  -63.9907885
Jun 5 -559.06374 8368.500  -50.4358031
Jul 5 -350.03422 8379.915 -194.8808212
Aug 5 -708.30090 8389.626  -81.3251146
Sep 5 -805.36725 8399.337   57.0302660
Oct 5 -227.68575 8409.670  137.0155584
Nov 5 -218.80451 8420.003  610.8011085
Dec 5  769.94558 8430.945 -570.8909342
> m$win
  s   t   l 
601  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
61  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1l3dv1291028702.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2l3dv1291028702.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3euug1291028702.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/4euug1291028702.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5ld9a1291028702.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6cgxm1291028702.tab") 
> 
> try(system("convert tmp/1l3dv1291028702.ps tmp/1l3dv1291028702.png",intern=TRUE))
character(0)
> try(system("convert tmp/2l3dv1291028702.ps tmp/2l3dv1291028702.png",intern=TRUE))
character(0)
> try(system("convert tmp/3euug1291028702.ps tmp/3euug1291028702.png",intern=TRUE))
character(0)
> try(system("convert tmp/4euug1291028702.ps tmp/4euug1291028702.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.979   0.618   6.609