R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-redhat-linux-gnu (64-bit)

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(206010
+ ,198112
+ ,194519
+ ,185705
+ ,180173
+ ,176142
+ ,203401
+ ,221902
+ ,197378
+ ,185001
+ ,176356
+ ,180449
+ ,180144
+ ,173666
+ ,165688
+ ,161570
+ ,156145
+ ,153730
+ ,182698
+ ,200765
+ ,176512
+ ,166618
+ ,158644
+ ,159585
+ ,163095
+ ,159044
+ ,155511
+ ,153745
+ ,150569
+ ,150605
+ ,179612
+ ,194690
+ ,189917
+ ,184128
+ ,175335
+ ,179566
+ ,181140
+ ,177876
+ ,175041
+ ,169292
+ ,166070
+ ,166972
+ ,206348
+ ,215706
+ ,202108
+ ,195411
+ ,193111
+ ,195198
+ ,198770
+ ,194163
+ ,190420
+ ,189733
+ ,186029
+ ,191531
+ ,232571
+ ,243477
+ ,227247
+ ,217859
+ ,208679
+ ,213188
+ ,216234
+ ,213586
+ ,209465
+ ,204045
+ ,200237
+ ,203666
+ ,241476
+ ,260307
+ ,243324
+ ,244460
+ ,233575
+ ,237217
+ ,235243
+ ,230354
+ ,227184
+ ,221678
+ ,217142
+ ,219452
+ ,256446
+ ,265845
+ ,248624
+ ,241114
+ ,229245
+ ,231805
+ ,219277
+ ,219313
+ ,212610
+ ,214771
+ ,211142
+ ,211457
+ ,240048
+ ,240636
+ ,230580
+ ,208795
+ ,197922
+ ,194596
+ ,194581
+ ,185686
+ ,178106
+ ,172608
+ ,167302
+ ,168053
+ ,202300
+ ,202388
+ ,182516
+ ,173476
+ ,166444
+ ,171297
+ ,169701
+ ,164182
+ ,161914
+ ,159612
+ ,151001
+ ,158114
+ ,186530
+ ,187069
+ ,174330
+ ,169362
+ ,166827
+ ,178037
+ ,186413
+ ,189226
+ ,191563
+ ,188906
+ ,186005
+ ,195309
+ ,223532
+ ,226899
+ ,214126
+ ,206903
+ ,204442
+ ,220375
+ ,214320
+ ,212588
+ ,205816
+ ,202196
+ ,195722
+ ,198563
+ ,229139
+ ,229527
+ ,211868
+ ,203555
+ ,195770)
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> ylab = ''
> xlab = ''
> main = ''
> #'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   -278.16702 204831.5   1456.67020
Feb  1  -4093.16961 202528.2   -323.01982
Mar  1  -8143.75571 200224.9   2437.87367
Apr  1 -11724.45070 197957.9   -528.47426
May  1 -16334.14604 195691.0    816.17817
Jun  1 -14155.66457 193447.1  -3149.46192
Jul  1  18393.65369 191203.3  -6195.93879
Aug  1  27148.94775 188965.4   5787.60679
Sep  1  11254.99492 186727.6   -604.60074
Oct  1   2771.38998 184642.5  -2412.84503
Nov  1  -4752.55030 182557.3  -1448.75400
Dec  1    -87.08401 180663.0   -126.87506
Jan  2   -278.16702 178768.6   1653.55317
Feb  2  -4093.16961 177020.5    738.67038
Mar  2  -8143.75571 175272.4  -1440.62892
Apr  2 -11724.45070 173640.3   -345.84054
May  2 -16334.14604 172008.2    470.94820
Jun  2 -14155.66457 170499.3  -2613.64637
Jul  2  18393.65369 168990.4  -4686.07772
Aug  2  27148.94775 167783.2   5832.83362
Sep  2  11254.99492 166576.0  -1319.00814
Oct  2   2771.38998 165865.0  -2018.42542
Nov  2  -4752.55030 165154.1  -1757.50736
Dec  2    -87.08401 164786.8  -5114.76118
Jan  3   -278.16702 164419.6  -1046.46571
Feb  3  -4093.16961 164623.5  -1486.32128
Mar  3  -8143.75571 164827.3  -1172.59334
Apr  3 -11724.45070 165889.6   -420.18337
May  3 -16334.14604 166951.9    -48.77305
Jun  3 -14155.66457 168550.2  -3789.49353
Jul  3  18393.65369 170148.4  -8930.05080
Aug  3  27148.94775 171823.0  -4281.96970
Sep  3  11254.99492 173497.6   5164.35830
Oct  3   2771.38998 175113.6   6243.04604
Nov  3  -4752.55030 176729.5   3358.06911
Dec  3    -87.08401 178261.9   1391.13637
Jan  4   -278.16702 179794.4   1623.75292
Feb  4  -4093.16961 181126.9    842.25742
Mar  4  -8143.75571 182459.4    725.34543
Apr  4 -11724.45070 183640.4  -2623.98176
May  4 -16334.14604 184821.5  -2417.30860
Jun  4 -14155.66457 186188.6  -5060.95601
Jul  4  18393.65369 187555.8    398.55979
Aug  4  27148.94775 189084.0   -526.96164
Sep  4  11254.99492 190612.2    240.76381
Oct  4   2771.38998 192272.1    367.51099
Nov  4  -4752.55030 193932.0   3931.59350
Dec  4    -87.08401 195803.6   -518.51369
Jan  5   -278.16702 197675.2   1372.92841
Feb  5  -4093.16961 199688.1  -1431.91446
Mar  5  -8143.75571 201700.9  -3137.17382
Apr  5 -11724.45070 203594.2  -2136.77795
May  5 -16334.14604 205487.5  -3124.38172
Jun  5 -14155.66457 207163.0  -1476.36964
Jul  5  18393.65369 208838.5   5338.80564
Aug  5  27148.94775 210384.9   5943.14868
Sep  5  11254.99492 211931.3   4060.73861
Oct  5   2771.38998 213159.8   1927.77761
Nov  5  -4752.55030 214388.4   -956.84804
Dec  5    -87.08401 215294.3  -2019.20948
Jan  6   -278.16702 216200.2    311.97838
Feb  6  -4093.16961 217346.3    332.82463
Mar  6  -8143.75571 218492.5   -883.74561
Apr  6 -11724.45070 220292.8  -4523.37217
May  6 -16334.14604 222093.1  -5521.99838
Jun  6 -14155.66457 224126.5  -6304.86114
Jul  6  18393.65369 226159.9  -3077.56069
Aug  6  27148.94775 227995.9   5162.12070
Sep  6  11254.99492 229832.0   2237.04897
Oct  6   2771.38998 231357.1  10331.49061
Nov  6  -4752.55030 232882.3   5445.26758
Dec  6    -87.08401 233922.5   3381.56215
Jan  7   -278.16702 234962.8    558.40600
Feb  7  -4093.16961 235387.8   -940.63410
Mar  7  -8143.75571 235812.8   -485.09070
Apr  7 -11724.45070 235782.7  -2380.25900
May  7 -16334.14604 235752.6  -2276.42695
Jun  7 -14155.66457 235292.8  -1685.12166
Jul  7  18393.65369 234833.0   3219.34684
Aug  7  27148.94775 233984.2   4711.84234
Sep  7  11254.99492 233135.4   4233.58474
Oct  7   2771.38998 232160.6   6181.98826
Nov  7  -4752.55030 231185.8   2811.72712
Dec  7    -87.08401 230018.5   1873.56146
Jan  8   -278.16702 228851.2  -9296.05492
Feb  8  -4093.16961 227219.4  -3813.26363
Mar  8  -8143.75571 225587.6  -4833.88883
Apr  8 -11724.45070 223497.4   2998.08847
May  8 -16334.14604 221407.1   6069.06612
Jun  8 -14155.66457 218949.2   6663.42752
Jul  8  18393.65369 216491.4   5162.95214
Aug  8  27148.94775 213541.0    -53.94868
Sep  8  11254.99492 210590.6   8734.39740
Oct  8   2771.38998 207069.7  -1046.12448
Nov  8  -4752.55030 203548.9   -874.31103
Dec  8    -87.08401 199944.8  -5261.70107
Jan  9   -278.16702 196340.7  -1481.54182
Feb  9  -4093.16961 193003.2  -3224.01974
Mar  9  -8143.75571 189665.7  -3415.91416
Apr  9 -11724.45070 186770.3  -2437.88963
May  9 -16334.14604 183875.0   -238.86474
Jun  9 -14155.66457 181610.1    598.55975
Jul  9  18393.65369 179345.2   4561.14745
Aug  9  27148.94775 177593.3  -2354.26287
Sep  9  11254.99492 175841.4  -4580.42629
Oct  9   2771.38998 174485.1  -3780.48004
Nov  9  -4752.55030 173128.7  -1932.19846
Dec  9    -87.08401 172071.8   -687.76218
Jan 10   -278.16702 171014.9  -1035.77661
Feb 10  -4093.16961 170181.2  -1905.98739
Mar 10  -8143.75571 169347.4    710.38533
Apr 10 -11724.45070 168951.9   2384.55197
May 10 -16334.14604 168556.4  -1221.28104
Jun 10 -14155.66457 169009.5   3260.13355
Jul 10  18393.65369 169462.6  -1326.28865
Aug 10  27148.94775 171115.5 -11195.49593
Sep 10  11254.99492 172768.5  -9693.45633
Oct 10   2771.38998 175451.4  -8860.80989
Nov 10  -4752.55030 178134.4  -6554.82812
Dec 10    -87.08401 181543.5  -3419.43314
Jan 11   -278.16702 184952.7   1738.51113
Feb 11  -4093.16961 188509.3   4809.88448
Mar 11  -8143.75571 192065.9   7640.84133
Apr 11 -11724.45070 195248.8   5381.69577
May 11 -16334.14604 198431.6   3907.55057
Jun 11 -14155.66457 201016.1   8448.56397
Jul 11  18393.65369 203600.6   1537.74059
Aug 11  27148.94775 205440.9  -5690.87775
Sep 11  11254.99492 207281.3  -4410.24921
Oct 11   2771.38998 208457.4  -4325.75261
Nov 11  -4752.55030 209633.5   -438.92069
Dec 11    -87.08401 210381.0  10081.05666
Jan 12   -278.16702 211128.6   3469.58330
Feb 12  -4093.16961 210948.7   5732.43006
Mar 12  -8143.75571 210768.9   3190.86031
Apr 12 -11724.45070 209906.1   4014.36682
May 12 -16334.14604 209043.3   3012.87367
Jun 12 -14155.66457 208095.2   4623.42918
Jul 12  18393.65369 207147.2   3598.14791
Aug 12  27148.94775 206054.8  -3676.76180
Sep 12  11254.99492 204962.4  -4349.42461
Oct 12   2771.38998 203714.4  -2930.81659
Nov 12  -4752.55030 202466.4  -1943.87323
> m$win
   s    t    l 
1431   19   13 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
144   2   2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/wessaorg/rcomp/tmp/14byi1293661730.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/wessaorg/rcomp/tmp/24byi1293661730.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/wessaorg/rcomp/tmp/3wkyl1293661730.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/wessaorg/rcomp/tmp/4wkyl1293661730.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/wessaorg/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/wessaorg/rcomp/tmp/533dx1293661730.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/wessaorg/rcomp/tmp/6euuz1293661730.tab") 
> 
> try(system("convert tmp/14byi1293661730.ps tmp/14byi1293661730.png",intern=TRUE))
character(0)
> try(system("convert tmp/24byi1293661730.ps tmp/24byi1293661730.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wkyl1293661730.ps tmp/3wkyl1293661730.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wkyl1293661730.ps tmp/4wkyl1293661730.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   1.91    0.13    2.11