R version 2.6.1 (2007-11-26)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(13328,12873,14000,13477,14237,13674,13529,14058,12975,14326,14008,16193,14483,14011,15057,14884,15414,14440,14900,15074,14442,15307,14938,17193,15528,14765,15838,15723,16150,15486,15986,15983,15692,16490,15686,18897,16316,15636,17163,16534,16518,16375,16290,16352,15943,16362,16393,19051,16747,16320,17910,16961,17480,17049,16879,17473,16998,17307,17418,20169,17871,17226,19062,17804,19100,18522,18060,18869,18127,18871,18890,21263,19547,18450,20254,19240,20216,19420,19415,20018,18652,19978,19509,21971)
> 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  -99.33842 13457.80  -30.458242
Feb 1 -831.41341 13539.45  164.961502
Mar 1  513.94006 13621.11 -135.047223
Apr 1 -219.38922 13704.21   -7.824961
May 1  354.85252 13787.32   94.826273
Jun 1 -297.52501 13872.40   99.121405
Jul 1 -343.90262 13957.49  -84.583384
Aug 1  -10.34012 14044.11   24.229140
Sep 1 -786.20558 14130.74 -369.530373
Oct 1  -30.85734 14223.33  133.527131
Nov 1 -362.79428 14315.92   54.869821
Dec 1 2112.97343 14414.58 -334.554192
Jan 2  -99.33842 14513.24   69.101350
Feb 2 -831.41341 14613.26  229.149702
Mar 2  513.94006 14713.29 -170.230413
Apr 2 -219.38922 14805.76  297.625832
May 2  354.85252 14898.24  160.911051
Jun 2 -297.52501 14977.58 -240.055341
Jul 2 -343.90262 15056.92  186.978345
Aug 2  -10.34012 15125.05  -40.713984
Sep 2 -786.20558 15193.18   35.021650
Oct 2  -30.85734 15260.91   76.944493
Nov 2 -362.79428 15328.64  -27.847477
Dec 2 2112.97343 15405.16 -325.133046
Jan 3  -99.33842 15481.68  145.660939
Feb 3 -831.41341 15570.45   25.958450
Mar 3  513.94006 15659.23 -335.172508
Apr 3 -219.38922 15755.50  186.886478
May 3  354.85252 15851.77  -56.625564
Jun 3 -297.52501 15948.57 -165.045134
Jul 3 -343.90262 16045.37  284.535374
Aug 3  -10.34012 16132.78 -139.443365
Sep 3 -786.20558 16220.20  258.005858
Oct 3  -30.85734 16290.05  230.806487
Nov 3 -362.79428 16359.90 -311.107699
Dec 3 2112.97343 16406.14  377.883379
Jan 4  -99.33842 16452.38  -37.045988
Feb 4 -831.41341 16478.35  -10.938038
Mar 4  513.94006 16504.32  144.741445
Apr 4 -219.38922 16522.70  230.684878
May 4  354.85252 16541.09 -377.942715
Jun 4 -297.52501 16567.34  105.182606
Jul 4 -343.90262 16593.59   40.308005
Aug 4  -10.34012 16638.21 -275.867492
Sep 4 -786.20558 16682.82   46.384974
Oct 4  -30.85734 16742.86 -349.997733
Nov 4 -362.79428 16802.89  -47.095253
Dec 4 2112.97343 16872.49   65.532974
Jan 5  -99.33842 16942.10  -95.759244
Feb 5 -831.41341 17019.62  131.791367
Mar 5  513.94006 17097.15  298.913511
Apr 5 -219.38922 17179.31    1.082936
May 5  354.85252 17261.47 -136.318666
Jun 5 -297.52501 17343.83    2.697490
Jul 5 -343.90262 17426.19 -203.286275
Aug 5  -10.34012 17513.38  -30.041208
Sep 5 -786.20558 17600.57  183.631822
Oct 5  -30.85734 17701.72 -363.863737
Nov 5 -362.79428 17802.87  -22.074110
Dec 5 2112.97343 17916.30  139.726646
Jan 6  -99.33842 18029.73  -59.393044
Feb 6 -831.41341 18143.48  -86.068794
Mar 6  513.94006 18257.23  290.826989
Apr 6 -219.38922 18370.00 -346.606971
May 6  354.85252 18482.76  262.388042
Jun 6 -297.52501 18595.78  223.742397
Jul 6 -343.90262 18708.81 -304.903171
Aug 6  -10.34012 18818.97   60.368394
Sep 6 -786.20558 18929.14  -15.932079
Oct 6  -30.85734 19033.61 -131.755407
Nov 6 -362.79428 19138.09  114.706451
Dec 6 2112.97343 19235.82  -85.789431
Jan 7  -99.33842 19333.54  312.794243
Feb 7 -831.41341 19419.75 -138.339049
Mar 7  513.94006 19505.96  234.099191
Apr 7 -219.38922 19561.33 -101.939841
May 7  354.85252 19616.70  244.450100
Jun 7 -297.52501 19669.64   47.889538
Jul 7 -343.90262 19722.57   36.329054
Aug 7  -10.34012 19773.19  255.154295
Sep 7 -786.20558 19823.80 -385.592502
Oct 7  -30.85734 19871.33  137.530610
Nov 7 -362.79428 19918.86  -47.061091
Dec 7 2112.97343 19964.19 -106.168306
> m$win
  s   t   l 
841  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
85  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/freestat/rcomp/tmp/1xl511204803319.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/freestat/rcomp/tmp/2b29e1204803319.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/freestat/rcomp/tmp/3rlvz1204803319.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/freestat/rcomp/tmp/4ywxt1204803319.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 
> 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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/5jrxm1204803319.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6gc691204803319.tab") 
> 
> system("convert tmp/1xl511204803319.ps tmp/1xl511204803319.png")
> system("convert tmp/2b29e1204803319.ps tmp/2b29e1204803319.png")
> system("convert tmp/3rlvz1204803319.ps tmp/3rlvz1204803319.png")
> system("convert tmp/4ywxt1204803319.ps tmp/4ywxt1204803319.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.815   0.842   1.920