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(274412,272433,268361,268586,264768,269974,304744,309365,308347,298427,289231,291975,294912,293488,290555,284736,281818,287854,316263,325412,326011,328282,317480,317539,313737,312276,309391,302950,300316,304035,333476,337698,335932,323931,313927,314485,313218,309664,302963,298989,298423,301631,329765,335083,327616,309119,295916,291413,291542,284678,276475,272566,264981,263290,296806,303598,286994,276427,266424,267153,268381,262522,255542,253158,243803,250741,280445,285257,270976,261076,255603,260376,263903,264291,263276,262572,256167,264221,293860)
> 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  -1596.321 275624.4   383.94791
Feb 1  -4697.680 277347.0  -216.31800
Mar 1  -9518.468 279069.6 -1190.15513
Apr 1 -12872.870 280782.1   676.79593
May 1 -17695.125 282494.5   -31.39969
Jun 1 -13276.256 284195.6  -945.32717
Jul 1  17163.044 285896.6  1684.31514
Aug 1  23370.793 287591.9 -1597.70239
Sep 1  16781.296 289287.2  2278.52531
Oct 1   7037.426 290896.9   492.71028
Nov 1  -2717.612 292506.5  -557.93771
Dec 1  -1978.227 293852.8   100.43963
Jan 2  -1596.321 295199.0  1309.29670
Feb 2  -4697.680 296575.6  1610.09657
Mar 2  -9518.468 297952.1  2121.32521
Apr 2 -12872.870 299777.5 -2168.63333
May 2 -17695.125 301602.9 -2089.73857
Jun 2 -13276.256 303636.0 -2505.72479
Jul 2  17163.044 305669.1 -6569.14122
Aug 2  23370.793 307547.4 -5506.20529
Sep 2  16781.296 309425.7  -196.02414
Oct 2   7037.426 311126.8 10117.72516
Nov 2  -2717.612 312828.0  7369.64148
Dec 2  -1978.227 314213.0  5304.26099
Jan 3  -1596.321 315598.0  -264.63977
Feb 3  -4697.680 316333.8   639.84921
Mar 3  -9518.468 317069.7  1839.76697
Apr 3 -12872.870 317127.9 -1305.02552
May 3 -17695.125 317186.1   825.03529
Jun 3 -13276.256 317013.3   298.00214
Jul 3  17163.044 316840.4  -527.46122
Aug 3  23370.793 316601.8 -2274.62491
Sep 3  16781.296 316363.2  2787.45664
Oct 3   7037.426 316058.7   834.86558
Nov 3  -2717.612 315754.2   890.44156
Dec 3  -1978.227 315458.2  1005.03025
Jan 4  -1596.321 315162.2  -347.90133
Feb 4  -4697.680 314700.0  -338.32880
Mar 4  -9518.468 314237.8 -1756.32750
Apr 4 -12872.870 313240.9 -1379.00456
May 4 -17695.125 312244.0  3874.17167
Jun 4 -13276.256 310644.0  4263.24310
Jul 4  17163.044 309044.1  3557.88431
Aug 4  23370.793 306920.3  4791.92546
Sep 4  16781.296 304796.5  6038.21183
Oct 4   7037.426 302193.0  -111.43842
Nov 4  -2717.612 299589.5  -955.92163
Dec 4  -1978.227 296654.2 -3262.93423
Jan 5  -1596.321 293718.8  -580.46710
Feb 5  -4697.680 290822.0 -1446.34761
Mar 5  -9518.468 287925.3 -1931.79935
Apr 5 -12872.870 285294.8   144.04717
May 5 -17695.125 282664.4    11.74700
Jun 5 -13276.256 280452.9 -3886.60126
Jul 5  17163.044 278241.3  1401.62028
Aug 5  23370.793 276362.9  3864.26610
Sep 5  16781.296 274484.5 -4271.84285
Oct 5   7037.426 272849.7 -3460.12393
Nov 5  -2717.612 271214.8 -2073.23798
Dec 5  -1978.227 269814.0  -682.79818
Jan 6  -1596.321 268413.2  1564.12134
Feb 6  -4697.680 267138.5    81.18596
Mar 6  -9518.468 265863.8  -803.32065
Apr 6 -12872.870 264729.1  1301.78952
May 6 -17695.125 263594.4 -2096.24700
Jun 6 -13276.256 262840.4  1176.86243
Jul 6  17163.044 262086.4  1195.54166
Aug 6  23370.793 262072.8  -186.56190
Sep 6  16781.296 262059.1 -7864.42022
Oct 6   7037.426 263090.5 -9051.90701
Nov 6  -2717.612 264121.8 -5801.22676
Dec 6  -1978.227 265598.7 -3244.48077
Jan 7  -1596.321 267075.6 -1576.25504
Feb 7  -4697.680 268640.5   348.20582
Mar 7  -9518.468 270205.4  2589.09547
Apr 7 -12872.870 271906.2  3538.65232
May 7 -17695.125 273607.1   255.06246
Jun 7 -13276.256 275416.1  2081.15600
Jul 7  17163.044 277225.1  -528.18067
> m$win
  s   t   l 
791  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
80  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1dpk81259939572.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2hyfq1259939572.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3aekk1259939573.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/4fea21259939573.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5b6k71259939573.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6xdsv1259939573.tab") 
> system("convert tmp/1dpk81259939572.ps tmp/1dpk81259939572.png")
> system("convert tmp/2hyfq1259939572.ps tmp/2hyfq1259939572.png")
> system("convert tmp/3aekk1259939573.ps tmp/3aekk1259939573.png")
> system("convert tmp/4fea21259939573.ps tmp/4fea21259939573.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.993   0.588   1.174