R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(13.7,13.7,13.7,1.3,1.3,1.3,-7.4,-7.4,-7.4,-12.9,-12.9,-12.9,-9.6,-9.6,-9.6,-11.1,-11.1,-11.1,-8.3,-8.3,-8.3,-2.7,-2.7,-2.7,5.1,5.1,5.1,4.6,4.6,4.6,5.6,5.6,5.6,5.1,5.1,5.1,0.8,0.8,0.8,6,6,6,9.3,9.3,9.3,8.7,8.7,8.7,11,11,11,8.5,8.5,8.5,4.4,4.4,4.4,2.5,2.5,2.5,0.3,0.3,0.3,-3,-3,-3)
> 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  1.12822201  11.5508553  1.02092273
Feb 1  1.49448728   9.2470288  2.95848390
Mar 1  1.86075254   6.9432024  4.89604507
Apr 1 -0.33791736   4.7394294 -3.10151201
May 1 -0.03659363   2.5356564 -1.19906272
Jun 1  0.24466912   0.4199664  0.63536444
Jul 1 -0.93451491  -1.6957235 -4.76976161
Aug 1 -0.71992790  -3.7610749 -2.91899725
Sep 1 -0.50534090  -5.8264262 -1.06823288
Oct 1 -0.88507593  -7.3860617 -4.62886237
Nov 1 -0.68481281  -8.9456972 -3.26949001
Dec 1 -0.62394691  -9.6140014 -2.66205174
Jan 2  1.12822201 -10.2823055 -0.44591647
Feb 2  1.49448728 -10.3267105 -0.76777680
Mar 2  1.86075254 -10.3711154 -1.08963712
Apr 2 -0.33791736  -9.8505634 -0.91151927
May 2 -0.03659363  -9.3300113 -1.73339504
Jun 2  0.24466912  -8.3753686 -2.96930055
Jul 2 -0.93451491  -7.4207258  0.05524073
Aug 2 -0.71992790  -6.1877623 -1.39230976
Sep 2 -0.50534090  -4.9547989 -2.83986024
Oct 2 -0.88507593  -3.5928415  1.77791744
Nov 2 -0.68481281  -2.2308842  0.21569697
Dec 2 -0.62394691  -0.9200338 -1.15601930
Jan 3  1.12822201   0.3908166  3.58096142
Feb 3  1.49448728   1.5029933  2.10251944
Mar 3  1.86075254   2.6151700  0.62407746
Apr 3 -0.33791736   3.4085488  1.52936860
May 3 -0.03659363   4.2019275  0.43466612
Jun 3  0.24466912   4.5131593 -0.15782845
Jul 3 -0.93451491   4.8243911  1.71012377
Aug 3 -0.71992790   4.6907447  1.62918320
Sep 3 -0.50534090   4.5570983  1.54824264
Oct 3 -0.88507593   4.3888563  1.59621965
Nov 3 -0.68481281   4.2206143  1.56419850
Dec 3 -0.62394691   4.2561741  1.46777277
Jan 4  1.12822201   4.2917340 -4.61995597
Feb 4  1.49448728   4.5424832 -5.23697050
Mar 4  1.86075254   4.7932325 -5.85398503
Apr 4 -0.33791736   5.2369703  1.10094706
May 4 -0.03659363   5.6807081  0.35588553
Jun 4  0.24466912   6.3303936 -0.57506272
Jul 4 -0.93451491   6.9800791  3.25443581
Aug 4 -0.71992790   7.6717036  2.34822434
Sep 4 -0.50534090   8.3633280  1.44201287
Oct 4 -0.88507593   8.7449394  0.84013652
Nov 4 -0.68481281   9.1265508  0.25826201
Dec 4 -0.62394691   9.1068526  0.21709433
Jan 5  1.12822201   9.0871544  0.78462363
Feb 5  1.49448728   8.7645111  0.74100165
Mar 5  1.86075254   8.4418678  0.69737966
Apr 5 -0.33791736   7.9449904  0.89292698
May 5 -0.03659363   7.4481130  1.08848067
Jun 5  0.24466912   6.7810549  1.47427597
Jul 5 -0.93451491   6.1139969 -0.77948195
Aug 5 -0.71992790   5.2565548 -0.13662691
Sep 5 -0.50534090   4.3991128  0.50622813
Oct 5 -0.88507593   3.4428535 -0.05777762
Nov 5 -0.68481281   2.4865943  0.69821848
Dec 5 -0.62394691   1.5547656  1.56918126
Jan 6  1.12822201   0.6229370 -1.45115897
Feb 6  1.49448728  -0.3151799 -0.87930742
Mar 6  1.86075254  -1.2532967 -0.30745586
Apr 6 -0.33791736  -2.1972927 -0.46478992
May 6 -0.03659363  -3.1412888  0.17788239
Jun 6  0.24466912  -4.0848966  0.84022743
> m$win
  s   t   l 
661  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
67  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/freestat/rcomp/tmp/1vj5g1293444529.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/freestat/rcomp/tmp/2vj5g1293444529.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/www/html/freestat/rcomp/tmp/36a4j1293444529.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/www/html/freestat/rcomp/tmp/4h2mm1293444529.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/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/5dt1d1293444529.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/freestat/rcomp/tmp/6nljx1293444529.tab") 
> 
> try(system("convert tmp/1vj5g1293444529.ps tmp/1vj5g1293444529.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vj5g1293444529.ps tmp/2vj5g1293444529.png",intern=TRUE))
character(0)
> try(system("convert tmp/36a4j1293444529.ps tmp/36a4j1293444529.png",intern=TRUE))
character(0)
> try(system("convert tmp/4h2mm1293444529.ps tmp/4h2mm1293444529.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.435   0.865   1.581