R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-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(37,30,47,35,30,43,82,40,47,19,52,136,80,42,54,66,81,63,137,72,107,58,36,52,79,77,54,84,48,96,83,66,61,53,30,74,69,59,42,65,70,100,63,105,82,81,75,102,121,98,76,77,63,37,35,23,40,29,37,51,20,28,13,22,25,13,16,13,16,17,9,17,25,14,8,7,10,7,10,3)
> 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  10.8239302 30.694969  -4.5188990
Feb 1  -1.0331025 33.734513  -2.7014100
Mar 1  -8.7472919 36.774056  18.9732356
Apr 1   0.2110631 39.847967  -5.0590302
May 1  -3.8306037 42.921878  -9.0912743
Jun 1   1.1688093 45.985154  -4.1539636
Jul 1  11.1681906 49.048431  21.7833787
Aug 1  -3.1936594 52.011785  -8.8181258
Sep 1   3.1259183 54.975140 -11.1010579
Oct 1 -12.4241262 57.518434 -26.0943074
Nov 1 -14.9741820 60.061727   6.9124545
Dec 1  17.7050474 63.114080  55.1808722
Jan 2  10.8239302 66.166433   3.0096364
Feb 2  -1.0331025 69.546497 -26.5133948
Mar 2  -8.7472919 72.926561 -10.1792693
Apr 2   0.2110631 74.507243  -8.7183061
May 2  -3.8306037 76.087925   8.7426790
Jun 2   1.1688093 75.357093 -13.5259020
Jul 2  11.1681906 74.626261  51.2055488
Aug 2  -3.1936594 74.254298   0.9393615
Sep 2   3.1259183 73.882335  29.9917466
Oct 2 -12.4241262 73.404550  -2.9804242
Nov 2 -14.9741820 72.926766 -21.9525837
Dec 2  17.7050474 71.737880 -37.4429274
Jan 3  10.8239302 70.548995  -2.3729247
Feb 3  -1.0331025 69.345125   8.6879771
Mar 3  -8.7472919 68.141256  -5.3939645
Apr 3   0.2110631 67.690909  16.0980281
May 3  -3.8306037 67.240561 -15.4099575
Jun 3   1.1688093 66.911309  27.9198813
Jul 3  11.1681906 66.582058   5.2497519
Aug 3  -3.1936594 65.441845   3.7518148
Sep 3   3.1259183 64.301632  -6.4275499
Oct 3 -12.4241262 63.433689   1.9904374
Nov 3 -14.9741820 62.565746 -17.5915641
Dec 3  17.7050474 62.734377  -6.4394242
Jan 4  10.8239302 62.903008  -4.7269379
Feb 4  -1.0331025 64.557004  -4.5239019
Mar 4  -8.7472919 66.211001 -15.4637094
Apr 4   0.2110631 69.068905  -4.2799682
May 4  -3.8306037 71.926809   1.9037949
Jun 4   1.1688093 75.381589  23.4496013
Jul 4  11.1681906 78.836370 -27.0045605
Aug 4  -3.1936594 81.860051  26.3336079
Sep 4   3.1259183 84.883733  -6.0096513
Oct 4 -12.4241262 85.859830   7.5642966
Nov 4 -14.9741820 86.835926   3.1382559
Dec 4  17.7050474 84.423827  -0.1288742
Jan 5  10.8239302 82.011728  28.1643421
Feb 5  -1.0331025 77.399248  21.6338543
Mar 5  -8.7472919 72.786769  11.9605231
Apr 5   0.2110631 67.578630   9.2103070
May 5  -3.8306037 62.370491   4.4601126
Jun 5   1.1688093 56.720668 -20.8894778
Jul 5  11.1681906 51.070846 -27.2390364
Aug 5  -3.1936594 45.500845 -19.3071852
Sep 5   3.1259183 39.930843  -3.0567616
Oct 5 -12.4241262 36.119094   5.3050317
Nov 5 -14.9741820 32.307346  19.6668363
Dec 5  17.7050474 30.092010   3.2029423
Jan 6  10.8239302 27.876675 -18.7006052
Feb 6  -1.0331025 26.044585   2.9885180
Mar 6  -8.7472919 24.212494  -2.4652023
Apr 6   0.2110631 22.412639  -0.6237019
May 6  -3.8306037 20.612783   8.2178203
Jun 6   1.1688093 19.272517  -7.4413267
Jul 6  11.1681906 17.932251 -13.1004420
Aug 6  -3.1936594 17.081217  -0.8875575
Sep 6   3.1259183 16.230182  -3.3561007
Oct 6 -12.4241262 15.465593  13.9585327
Nov 6 -14.9741820 14.701005   9.2731774
Dec 6  17.7050474 13.728748 -14.4337950
Jan 7  10.8239302 12.756491   1.4195791
Feb 7  -1.0331025 11.708589   3.3245135
Mar 7  -8.7472919 10.660687   6.0866045
Apr 7   0.2110631  9.583485  -2.7945477
May 7  -3.8306037  8.506282   5.3243220
Jun 7   1.1688093  7.373991  -1.5428002
Jul 7  11.1681906  6.241700  -7.4098905
Aug 7  -3.1936594  5.056570   1.1370897
> m$win
  s   t   l 
801  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
81  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1j4wj1322321310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2d11i1322321310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3xui41322321310.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/4zjlu1322321310.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/596uu1322321310.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6csj91322321310.tab") 
> 
> try(system("convert tmp/1j4wj1322321310.ps tmp/1j4wj1322321310.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d11i1322321310.ps tmp/2d11i1322321310.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xui41322321310.ps tmp/3xui41322321310.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zjlu1322321310.ps tmp/4zjlu1322321310.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.377   0.259   2.028