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(4.2,4.19,4.19,4.19,4.19,4.18,4.2,4.19,4.17,4.21,4.22,4.23,4.21,4.23,4.23,4.22,4.25,4.28,4.3,4.32,4.33,4.32,4.34,4.33,4.31,4.31,4.3,4.3,4.29,4.33,4.32,4.32,4.35,4.37,4.39,4.4,4.41,4.44,4.47,4.47,4.47,4.48,4.47,4.48,4.46,4.44,4.43,4.41,4.41,4.38,4.35,4.37,4.4,4.39,4.36,4.34,4.33,4.33,4.34,4.34,4.35,4.37,4.39,4.4,4.38,4.37,4.36,4.33,4.33,4.33,4.32,4.33,4.34)
> par8 = 'TRUE'
> 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 -0.0004307551 4.184053  0.0163781352
Feb 1  0.0007235163 4.186219  0.0030576224
Mar 1 -0.0022237392 4.188385  0.0038386365
Apr 1 -0.0064565874 4.190823  0.0056333740
May 1  0.0072460626 4.193261 -0.0105073867
Jun 1  0.0111127957 4.195846 -0.0269589381
Jul 1  0.0057145993 4.198431 -0.0041455600
Aug 1 -0.0071080199 4.201046 -0.0039382825
Sep 1 -0.0085799742 4.203662 -0.0250816701
Oct 1 -0.0019402674 4.207563  0.0043768910
Nov 1  0.0015610813 4.211465  0.0069738102
Dec 1  0.0003812681 4.218150  0.0114690418
Jan 2 -0.0004307551 4.224834 -0.0144035164
Feb 2  0.0007235163 4.233847 -0.0045701457
Mar 2 -0.0022237392 4.242859 -0.0106352480
Apr 2 -0.0064565874 4.253244 -0.0267870329
May 2  0.0072460626 4.263628 -0.0208743160
Jun 2  0.0111127957 4.272894 -0.0040069548
Jul 2  0.0057145993 4.282160  0.0121253359
Aug 2 -0.0071080199 4.289779  0.0373291899
Sep 2 -0.0085799742 4.297398  0.0411823790
Oct 2 -0.0019402674 4.303133  0.0188075995
Nov 2  0.0015610813 4.308868  0.0295711780
Dec 2  0.0003812681 4.311774  0.0178443449
Jan 3 -0.0004307551 4.314681 -0.0042502782
Feb 3  0.0007235163 4.316069 -0.0067923765
Mar 3 -0.0022237392 4.317457 -0.0152329478
Apr 3 -0.0064565874 4.320978 -0.0145216272
May 3  0.0072460626 4.324500 -0.0417458048
Jun 3  0.0111127957 4.331341 -0.0124533703
Jul 3  0.0057145993 4.338181 -0.0238960064
Aug 3 -0.0071080199 4.348670 -0.0215619324
Sep 3 -0.0085799742 4.359158 -0.0005785233
Oct 3 -0.0019402674 4.372788 -0.0008482234
Nov 3  0.0015610813 4.386418  0.0020204345
Dec 3  0.0003812681 4.400123 -0.0005046064
Jan 4 -0.0004307551 4.413828 -0.0033974372
Feb 4  0.0007235163 4.424760  0.0145160075
Mar 4 -0.0022237392 4.435693  0.0365309791
Apr 4 -0.0064565874 4.441651  0.0348056965
May 4  0.0072460626 4.447609  0.0151449157
Jun 4  0.0111127957 4.448951  0.0199365675
Jul 4  0.0057145993 4.450292  0.0139931487
Aug 4 -0.0071080199 4.446502  0.0406064055
Sep 4 -0.0085799742 4.442711  0.0258689972
Oct 4 -0.0019402674 4.434788  0.0071527377
Nov 4  0.0015610813 4.426864  0.0015748362
Dec 4  0.0003812681 4.418003 -0.0083843216
Jan 5 -0.0004307551 4.409142  0.0012887307
Feb 5  0.0007235163 4.399730 -0.0204536101
Mar 5 -0.0022237392 4.390318 -0.0380944240
Apr 5 -0.0064565874 4.381775 -0.0053180577
May 5  0.0072460626 4.373231  0.0195228105
Jun 5  0.0111127957 4.367272  0.0116153297
Jul 5  0.0057145993 4.361313 -0.0070272217
Aug 5 -0.0071080199 4.358372 -0.0112638228
Sep 5 -0.0085799742 4.355431 -0.0168510889
Oct 5 -0.0019402674 4.355000 -0.0230601826
Nov 5  0.0015610813 4.354570 -0.0161309183
Dec 5  0.0003812681 4.354716 -0.0150977096
Jan 6 -0.0004307551 4.354863 -0.0044322908
Feb 6  0.0007235163 4.354858  0.0144182795
Mar 6 -0.0022237392 4.354853  0.0373703766
Apr 6 -0.0064565874 4.353406  0.0530504523
May 6  0.0072460626 4.351959  0.0207950299
Jun 6  0.0111127957 4.349619  0.0092678399
Jul 6  0.0057145993 4.347280  0.0070055793
Aug 6 -0.0071080199 4.344694 -0.0075861446
Sep 6 -0.0085799742 4.342109 -0.0035285335
Oct 6 -0.0019402674 4.339088 -0.0071481276
Nov 6  0.0015610813 4.336068 -0.0176293638
Dec 6  0.0003812681 4.332720 -0.0031012422
Jan 7 -0.0004307551 4.329372  0.0110590895
> m$win
  s   t   l 
731  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
74  2  2 
> m$inner
[1] 1
> m$outer
[1] 15
> postscript(file="/var/www/html/rcomp/tmp/1w5z01243770339.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/250vy1243770339.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/34grd1243770339.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/4oub71243770339.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/568m91243770339.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6n88b1243770339.tab") 
> 
> system("convert tmp/1w5z01243770339.ps tmp/1w5z01243770339.png")
> system("convert tmp/250vy1243770339.ps tmp/250vy1243770339.png")
> system("convert tmp/34grd1243770339.ps tmp/34grd1243770339.png")
> system("convert tmp/4oub71243770339.ps tmp/4oub71243770339.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.000   0.619   1.293