R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(547612,563280,581302,572273,518654,520579,530577,540324,547970,555654,551174,548604,563668,586111,604378,600991,544686,537034,551531,563250,574761,580112,575093,557560,564478,580523,596594,586570,536214,523597,536535,536322,532638,528222,516141,501866,506174,517945,533590,528379,477580,469357,490243,492622,507561,516922,514258,509846,527070,541657,564591,555362,498662,511038,525919,531673,548854,560576,557274,565742,587625,619916,625809,619567,572942,572775,574205,579799,590072,593408,597141,595404,612117,628232,628884,620735,569028,567456,573100,584428,589379,590865,595454,594167,611324,612613,610763,593530,542722,536662,543599,555332,560854,562325,554788,547344,565464,577992,579714,569323,506971,500857,509127,509933,517009,519164,512238,509239,518585,522975,525192,516847,455626,454724,461251,470439,474605,476049,471067,470984,502831,512927,509673,484015,431328,436087,442867,447988,460070,467037,460170,464196,485025)
> 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  11766.677 539202.5  -3357.177061
Feb  1  25965.145 540867.2  -3552.319560
Mar  1  35310.440 542531.8   3459.710985
Apr  1  25573.997 544185.8   2513.215202
May  1 -27824.357 545839.7    638.629616
Jun  1 -29648.355 547521.6   2705.763659
Jul  1 -19378.262 549203.5    751.805880
Aug  1 -12300.119 550918.1   1706.036975
Sep  1  -3539.521 552632.7  -1123.187722
Oct  1   1323.327 554393.8    -63.121233
Nov  1  -2186.276 556154.9  -2794.603524
Dec  1  -5062.695 558112.7  -4445.993428
Jan  2  11766.677 560070.5  -8169.173554
Feb  2  25965.145 562114.5  -1968.662414
Mar  2  35310.440 564158.5   4909.021771
Apr  2  25573.997 566185.3   9231.653557
May  2 -27824.357 568212.2   4298.195540
Jun  2 -29648.355 569277.8  -2595.412901
Jul  2 -19378.262 570343.4    565.886836
Aug  2 -12300.119 570039.0   5511.124797
Sep  2  -3539.521 569734.6   8565.906966
Oct  2   1323.327 568664.2  10124.453822
Nov  2  -2186.276 567593.8   9685.451898
Dec  2  -5062.695 566143.1  -3520.393977
Jan  3  11766.677 564692.4 -11981.030074
Feb  3  25965.145 562293.8  -7735.967237
Mar  3  35310.440 559895.3   1388.268645
Apr  3  25573.997 556336.7   4659.348512
May  3 -27824.357 552778.0  11260.338577
Jun  3 -29648.355 548219.4   5025.911164
Jul  3 -19378.262 543660.9  12252.391929
Aug  3 -12300.119 538261.0  10361.103845
Sep  3  -3539.521 532861.2   3316.359969
Oct  3   1323.327 527273.4   -374.717413
Nov  3  -2186.276 521685.6  -3358.343575
Dec  3  -5062.695 516988.7 -10059.990864
Jan  4  11766.677 512291.8 -17884.428374
Feb  4  25965.145 509287.2 -17307.357726
Mar  4  35310.440 506282.7  -8003.114034
Apr  4  25573.997 505482.2  -2677.180539
May  4 -27824.357 504681.7    722.663152
Jun  4 -29648.355 505654.7  -6649.308068
Jul  4 -19378.262 506627.6   2993.628889
Aug  4 -12300.119 508537.3  -3615.200583
Sep  4  -3539.521 510447.0    653.514154
Oct  4   1323.327 512684.1   2914.546799
Nov  4  -2186.276 514921.2   1523.030665
Dec  4  -5062.695 517641.1  -2732.411513
Jan  5  11766.677 520361.0  -5057.643913
Feb  5  25965.145 523568.6  -7876.722479
Mar  5  35310.440 526776.2   2504.372000
Apr  5  25573.997 530538.5   -750.460894
May  5 -27824.357 534300.7  -7814.383592
Jun  5 -29648.355 538885.4   1800.905982
Jul  5 -19378.262 543470.2   1827.103733
Aug  5 -12300.119 548871.7  -4898.586490
Sep  5  -3539.521 554273.3  -1879.732505
Oct  5   1323.327 559931.7   -678.989114
Nov  5  -2186.276 565590.1  -6129.794504
Dec  5  -5062.695 570849.1    -44.439410
Jan  6  11766.677 576108.2   -249.874537
Feb  6  25965.145 580319.5  13631.371146
Mar  6  35310.440 584530.8   5967.789874
Apr  6  25573.997 587631.2   6361.791635
May  6 -27824.357 590731.7  10034.703593
Jun  6 -29648.355 592765.3   9658.038949
Jul  6 -19378.262 594799.0  -1215.717518
Aug  6 -12300.119 595691.2  -3592.046446
Sep  6  -3539.521 596583.4  -2971.831166
Oct  6   1323.327 596722.5  -4637.777034
Nov  6  -2186.276 596861.5   2465.728318
Dec  6  -5062.695 596812.2   3654.446241
Jan  7  11766.677 596762.9   3587.373944
Feb  7  25965.145 596744.5   5522.326979
Mar  7  35310.440 596726.1  -3152.546942
Apr  7  25573.997 596511.8  -1350.819487
May  7 -27824.357 596297.5    554.818164
Jun  7 -29648.355 595957.3   1147.083946
Jul  7 -19378.262 595617.0  -3138.742094
Aug  7 -12300.119 594801.2   1926.954772
Sep  7  -3539.521 593985.3  -1066.804155
Oct  7   1323.327 592282.7  -2741.014245
Nov  7  -2186.276 590580.0   7060.226885
Dec  7  -5062.695 588135.5  11094.148687
Jan  8  11766.677 585691.0  13866.280269
Feb  8  25965.145 582946.8   3701.048886
Mar  8  35310.440 580202.6  -4750.009453
Apr  8  25573.997 577084.6  -9128.621317
May  8 -27824.357 573966.7  -3420.322983
Jun  8 -29648.355 570650.9  -4340.581595
Jul  8 -19378.262 567335.2  -4357.932030
Aug  8 -12300.119 564478.1   3154.010767
Sep  8  -3539.521 561621.0   2772.497773
Oct  8   1323.327 559096.5   1905.209577
Nov  8  -2186.276 556571.9    402.372601
Dec  8  -5062.695 553627.2  -1220.550626
Jan  9  11766.677 550682.6   3014.735927
Feb  9  25965.145 547232.7   4794.203924
Mar  9  35310.440 543782.7    620.844966
Apr  9  25573.997 540126.9   3622.131550
May  9 -27824.357 536471.0  -1675.671668
Jun  9 -29648.355 532715.1  -2209.753494
Jul  9 -19378.262 528959.2   -453.927142
Aug  9 -12300.119 524855.4  -2622.299352
Sep  9  -3539.521 520751.6   -203.127354
Oct  9   1323.327 516503.1   1337.527984
Nov  9  -2186.276 512254.6   2169.634543
Dec  9  -5062.695 508175.8   6125.849561
Jan 10  11766.677 504097.0   2721.274359
Feb 10  25965.145 500288.0  -3278.131425
Mar 10  35310.440 496478.9  -6597.364164
Apr 10  25573.997 492960.1  -1687.126739
May 10 -27824.357 489441.3  -5990.979118
Jun 10 -29648.355 486857.2  -2484.811769
Jul 10 -19378.262 484273.0  -3643.736243
Aug 10 -12300.119 482733.0      6.081365
Sep 10  -3539.521 481193.1  -3048.556818
Oct 10   1323.327 479700.9  -4975.228099
Nov 10  -2186.276 478208.7  -4955.448160
Dec 10  -5062.695 476499.6   -452.914909
Jan 11  11766.677 474790.5  16273.828122
Feb 11  25965.145 473207.1  13754.763381
Mar 11  35310.440 471623.7   2738.871685
Apr 11  25573.997 470390.3 -11949.344330
May 11 -27824.357 469157.0 -10004.650149
Jun 11 -29648.355 468355.1  -2619.707409
Jul 11 -19378.262 467553.1  -5307.856492
Aug 11 -12300.119 466787.7  -6499.557726
Sep 11  -3539.521 466022.2  -2412.714753
Oct 11   1323.327 465363.2    350.454836
Nov 11  -2186.276 464704.2  -2347.924355
Dec 11  -5062.695 464213.7   5044.947474
Jan 12  11766.677 463723.3   9535.029083
> m$win
   s    t    l 
1331   19   13 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
134   2   2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/rcomp/tmp/1jr541322677405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/rcomp/tmp/2ia7k1322677405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/rcomp/tmp/3eyjd1322677405.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/rcomp/tmp/4yt7w1322677405.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/5kmet1322677405.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/rcomp/tmp/6j8li1322677405.tab") 
> 
> try(system("convert tmp/1jr541322677405.ps tmp/1jr541322677405.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ia7k1322677405.ps tmp/2ia7k1322677405.png",intern=TRUE))
character(0)
> try(system("convert tmp/3eyjd1322677405.ps tmp/3eyjd1322677405.png",intern=TRUE))
character(0)
> try(system("convert tmp/4yt7w1322677405.ps tmp/4yt7w1322677405.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.196   0.348   2.525