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

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> x <- c(0.0314796223103059
+ ,-3.00870920563557
+ ,-2.07677512619799
+ ,-1.25010391965540
+ ,0.817975239137125
+ ,0.0252076485413113
+ ,0.554937772830776
+ ,0.230027371950115
+ ,2.35672227418686
+ ,1.41350455171120
+ ,2.73311719024401
+ ,1.31551925971717
+ ,-2.70076272244080
+ ,-0.721411049152714
+ ,-0.149388576811997
+ ,-0.118199629770334
+ ,-0.676562489695275
+ ,1.79699928690761
+ ,1.79845572032988
+ ,0.245100010770855
+ ,1.80710848932636
+ ,-1.75934771184948
+ ,-0.0186697168761931
+ ,0.189651523600062
+ ,-1.84149562719087
+ ,-1.07019530156943
+ ,-0.507291477584104
+ ,0.866365633831705
+ ,-1.76077926699189
+ ,-0.580719393339347
+ ,-0.435702079860853
+ ,-0.994868534845203
+ ,1.63136048315789
+ ,-1.1949403709466
+ ,-1.00525975426991
+ ,1.32302234837564
+ ,-0.628357549594746
+ ,0.632048410440518
+ ,-2.16903155809288
+ ,2.53779364144266
+ ,-0.632933703679292
+ ,-1.41749196342200
+ ,-0.455343045381255
+ ,0.812255211942954
+ ,0.627897309219833
+ ,0.650904313655623
+ ,-1.29800419154382
+ ,0.74391671726854
+ ,-1.50461634127457
+ ,-1.42734677658523
+ ,0.263353807408564
+ ,-0.430830854870631
+ ,0.379576092518008
+ ,1.70309353400146
+ ,-3.12314448117342
+ ,-1.32526207118689
+ ,-0.60032490743804
+ ,1.23607137604666
+ ,0.738007075905376
+ ,0.899100896289585)
> 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 -1.19588792 -0.61436538  1.841732927
Feb 1 -0.98896366 -0.47765790 -1.542087644
Mar 1 -0.80037317 -0.34095042 -0.935451537
Apr 1  0.44574196 -0.22185868 -1.473987198
May 1 -0.25252714 -0.10276695  1.173269324
Jun 1  0.42785722 -0.00180784 -0.400841735
Jul 1 -0.20929721  0.09915127  0.665083718
Aug 1 -0.09586532  0.20197251  0.123920180
Sep 1  1.26305998  0.30479375  0.788868543
Oct 1  0.14971653  0.38773006  0.876057965
Nov 1  0.29228831  0.47066636  1.970162518
Dec 1  0.96424959  0.48494017 -0.133670495
Jan 2 -1.19588792  0.49921397 -2.004088772
Feb 2 -0.98896366  0.47347544 -0.205922824
Mar 2 -0.80037317  0.44773690  0.203247693
Apr 2  0.44574196  0.35371680 -0.917658388
May 2 -0.25252714  0.25969669 -0.683732046
Jun 2  0.42785722  0.17551333  1.193628734
Jul 2 -0.20929721  0.09132997  1.916422967
Aug 2 -0.09586532  0.06139369  0.279571639
Sep 2  1.26305998  0.03145741  0.512591098
Oct 2  0.14971653 -0.03137079 -1.877693448
Nov 2  0.29228831 -0.09419900 -0.216759029
Dec 2  0.96424959 -0.20393650 -0.570661567
Jan 3 -1.19588792 -0.31367400 -0.331933708
Feb 3 -0.98896366 -0.39026810  0.309036465
Mar 3 -0.80037317 -0.46686221  0.759943907
Apr 3  0.44574196 -0.47739940  0.898023074
May 3 -0.25252714 -0.48793659 -1.020315540
Jun 3  0.42785722 -0.46502647 -0.543550149
Jul 3 -0.20929721 -0.44211635  0.215711480
Aug 3 -0.09586532 -0.39278250 -0.506220716
Sep 3  1.26305998 -0.34344866  0.711749160
Oct 3  0.14971653 -0.27697051 -1.067686391
Nov 3  0.29228831 -0.21049236 -1.087055702
Dec 3  0.96424959 -0.16184678  0.520619544
Jan 4 -1.19588792 -0.11320121  0.680731578
Feb 4 -0.98896366 -0.07759061  1.698602680
Mar 4 -0.80037317 -0.04198001 -1.326678375
Apr 4  0.44574196 -0.03240456  2.124456242
May 4 -0.25252714 -0.02282911 -0.357577454
Jun 4  0.42785722 -0.07015228 -1.775196904
Jul 4 -0.20929721 -0.11747545 -0.128570379
Aug 4 -0.09586532 -0.17393026  1.082050792
Sep 4  1.26305998 -0.23038508 -0.404777598
Oct 4  0.14971653 -0.22355278  0.724740566
Nov 4  0.29228831 -0.21672049 -1.373572010
Dec 4  0.96424959 -0.21333771 -0.006995159
Jan 5 -1.19588792 -0.20995493 -0.098773487
Feb 5 -0.98896366 -0.26789290 -0.170490212
Mar 5 -0.80037317 -0.32583087  1.389557853
Apr 5  0.44574196 -0.33224003 -0.544332787
May 5 -0.25252714 -0.33864918  0.970752413
Jun 5  0.42785722 -0.32467600  1.599912311
Jul 5 -0.20929721 -0.31070282 -2.603144451
Aug 5 -0.09586532 -0.30667830 -0.922718453
Sep 5  1.26305998 -0.30265379 -1.560731102
Oct 5  0.14971653 -0.30115386  1.387508708
Nov 5  0.29228831 -0.29965394  0.745372704
Dec 5  0.96424959 -0.29283862  0.227689933
> 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$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1z44h1259788618.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2pu491259788618.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/31or51259788618.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/453r81259788618.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5np6z1259788619.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6gy721259788619.tab") 
> system("convert tmp/1z44h1259788618.ps tmp/1z44h1259788618.png")
> system("convert tmp/2pu491259788618.ps tmp/2pu491259788618.png")
> system("convert tmp/31or51259788618.ps tmp/31or51259788618.png")
> system("convert tmp/453r81259788618.ps tmp/453r81259788618.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.024   0.632   2.298