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(3106.54,3125.67,3039.71,3051.67,3112.83,3228.01,3223.98,3328.8,3264.26,3394.14,3549.25,3744.63,3839.25,3912.28,3911.06,3675.8,3703.32,3795.91,3906.01,4070.78,4144.38,4140.3,4388.53,4433.57,4305.23,4471.65,4614.76,4697.86,4639.4,4384.47,4350.83,4325.29,4441.82,4162.5,4127.47,3722.23,3757.12,3719.52,3925.43,3751.41,3168.22,2994.38,3136,2672.2,2100.18,1881.46,1908.64,1900.09,1696.58,1748.74,1953.35,2071.37,2030.98,2169.14,2229.85,2480.93,2525.93,2475.14,2529.66,2453.37,2386.53,2517.3,2457.46,2589.73,2679.07,2506.13,2592.31)
> 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 -44.876654 2944.314  207.102736
Feb 1  19.373532 3001.769  104.527154
Mar 1  84.073878 3059.225 -103.588587
Apr 1  72.827612 3118.515 -139.673000
May 1 -11.767127 3177.806  -53.208940
Jun 1 -49.411339 3237.826   39.595034
Jul 1  15.731207 3297.847  -89.597749
Aug 1  48.907418 3358.561  -78.668238
Sep 1 -17.858819 3419.275 -137.156277
Oct 1 -91.931576 3483.246    2.825701
Nov 1   8.603735 3547.217   -6.570390
Dec 1 -33.671812 3602.495  175.807073
Jan 2 -44.876654 3657.773  226.353833
Feb 2  19.373532 3714.260  178.646578
Mar 2  84.073878 3770.747   56.239164
Apr 2  72.827612 3828.382 -225.410074
May 2 -11.767127 3886.018 -170.930838
Jun 2 -49.411339 3941.656  -96.334638
Jul 2  15.731207 3997.294 -107.015195
Aug 2  48.907418 4058.771  -36.898614
Sep 2 -17.858819 4120.248   41.990416
Oct 2 -91.931576 4190.708   41.523427
Nov 2   8.603735 4261.168  118.758370
Dec 2 -33.671812 4317.345  149.896818
Jan 3 -44.876654 4373.522  -23.415438
Feb 3  19.373532 4401.211   51.065592
Mar 3  84.073878 4428.900  101.786464
Apr 3  72.827612 4425.218  199.813925
May 3 -11.767127 4421.537  229.629858
Jun 3 -49.411339 4383.483   50.397883
Jul 3  15.731207 4345.430  -10.330849
Aug 3  48.907418 4281.338   -4.955000
Sep 3 -17.858819 4217.246  242.433298
Oct 3 -91.931576 4129.845  124.586518
Nov 3   8.603735 4042.445   76.421669
Dec 3 -33.671812 3931.907 -176.005058
Jan 4 -44.876654 3821.369  -19.372488
Feb 4  19.373532 3677.752   22.394350
Mar 4  84.073878 3534.135  307.221028
Apr 4  72.827612 3360.381  318.201445
May 4 -11.767127 3186.627   -6.639666
Jun 4 -49.411339 3004.905   38.885853
Jul 4  15.731207 2823.184  297.084615
Aug 4  48.907418 2650.167  -26.874063
Sep 4 -17.858819 2477.149 -359.110292
Oct 4 -91.931576 2339.030 -365.638592
Nov 4   8.603735 2200.911 -300.874961
Dec 4 -33.671812 2123.890 -190.128370
Jan 5 -44.876654 2046.869 -305.412482
Feb 5  19.373532 2037.521 -308.154074
Mar 5  84.073878 2028.172 -158.895825
Apr 5  72.827612 2072.402  -73.859445
May 5 -11.767127 2116.632  -73.884593
Jun 5 -49.411339 2177.638   40.913634
Jul 5  15.731207 2238.644  -24.524897
Aug 5  48.907418 2294.787  137.235175
Sep 5 -17.858819 2350.931  192.857695
Oct 5 -91.931576 2388.321  178.750959
Nov 5   8.603735 2425.710   95.346154
Dec 5 -33.671812 2452.167   34.874820
Jan 6 -44.876654 2478.624  -47.217218
Feb 6  19.373532 2502.165   -4.238689
Mar 6  84.073878 2525.706 -152.320319
Apr 6  72.827612 2546.684  -29.781780
May 6 -11.767127 2567.662  123.175231
Jun 6 -49.411339 2587.209  -31.667366
Jul 6  15.731207 2606.756  -30.176721
> m$win
  s   t   l 
671  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
68  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/freestat/rcomp/tmp/12vf71293630006.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/freestat/rcomp/tmp/2d4fa1293630006.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3d4fa1293630006.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/4nvwd1293630006.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/5j5um1293630006.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6n6as1293630006.tab") 
> 
> try(system("convert tmp/12vf71293630006.ps tmp/12vf71293630006.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d4fa1293630006.ps tmp/2d4fa1293630006.png",intern=TRUE))
character(0)
> try(system("convert tmp/3d4fa1293630006.ps tmp/3d4fa1293630006.png",intern=TRUE))
character(0)
> try(system("convert tmp/4nvwd1293630006.ps tmp/4nvwd1293630006.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.445   0.875   1.578