R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(989236,1008380,1207763,1368839,1469798,1498721,1761769,1653214,1599104,1421179,1163995,1037735,1015407,1039210,1258049,1469445,1552346,1549144,1785895,1662335,1629440,1467430,1202209,1076982,1039367,1063449,1335135,1491602,1591972,1641248,1898849,1798580,1762444,1622044,1368955,1262973,1195650,1269530,1479279,1607819,1712466,1721766,1949843,1821326,1757802,1590367,1260647,1149235,1016367,1027885,1262159,1520854,1544144,1564709,1821776,1741365,1623386,1498658,1241822,1136029)
> 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 -379171.70 1338624  29784.12363
Feb 1 -350271.44 1340638  18013.68734
Mar 1 -125070.37 1342652  -9818.55158
Apr 1   56142.81 1344913 -32216.73258
May 1  136554.64 1347174 -13930.55626
Jun 1  156508.48 1349564  -7351.21568
Jul 1  403998.71 1351954   5816.73352
Aug 1  295352.71 1354714   3147.42821
Sep 1  234040.33 1357474   7589.49021
Oct 1   78443.98 1362469 -19733.92541
Nov 1 -195062.78 1367464  -8405.93213
Dec 1 -311465.33 1372173 -22973.05505
Jan 2 -379171.70 1376883  17695.63552
Feb 2 -350271.44 1380038   9443.16043
Mar 2 -125070.37 1383193    -74.11730
Apr 2   56142.81 1385853  27449.51519
May 2  136554.64 1388512  27279.50500
Jun 2  156508.48 1390736   1899.24055
Jul 2  403998.71 1392961 -11064.41528
Aug 2  295352.71 1395331 -28348.26034
Sep 2  234040.33 1397700  -2300.73809
Oct 2   78443.98 1401751 -12764.53284
Nov 2 -195062.78 1405801  -8528.91869
Dec 2 -311465.33 1413025 -24578.04287
Jan 3 -379171.70 1420250  -1711.35356
Feb 3 -350271.44 1430858 -17137.74616
Mar 3 -125070.37 1441466  18739.05860
Apr 3   56142.81 1454395 -18935.40528
May 3  136554.64 1467323 -11905.51184
Jun 3  156508.48 1481699   3040.61802
Jul 3  403998.71 1496075  -1224.64352
Aug 3  295352.71 1510348  -7120.93481
Sep 3  234040.33 1524622   3782.14120
Oct 3   78443.98 1536242   7357.55527
Nov 3 -195062.78 1547863  16154.37825
Dec 3 -311465.33 1555117  19321.20546
Jan 4 -379171.70 1562371  12450.84617
Feb 4 -350271.44 1564205  55596.91089
Mar 4 -125070.37 1566038  38311.17297
Apr 4   56142.81 1561694 -10018.16063
May 4  136554.64 1557350  18560.86309
Jun 4  156508.48 1546085  19172.35449
Jul 4  403998.71 1534820  11024.45450
Aug 4  295352.71 1519030   6942.97008
Sep 4  234040.33 1503241  20520.85295
Oct 4   78443.98 1488173  23750.41899
Nov 4 -195062.78 1473104 -17394.60606
Dec 4 -311465.33 1460665     35.40734
Jan 5 -379171.70 1448225 -52686.76576
Feb 5 -350271.44 1438804 -60647.72596
Mar 5 -125070.37 1429383 -42153.48878
Apr 5   56142.81 1427207  37503.71486
May 5  136554.64 1425032 -17442.72418
Jun 5  156508.48 1424035 -15834.77259
Jul 5  403998.71 1423039  -5261.21239
Aug 5  295352.71 1422697  23315.01842
Sep 5  234040.33 1422356 -33010.38347
Oct 5   78443.98 1422551  -2336.98522
Nov 5 -195062.78 1422746  14138.82193
Dec 5 -311465.33 1423326  24168.44819
> m$win
  s   t   l 
601  19  13 
> m$deg
s t l 
0 1 1 
> m$jump
 s  t  l 
61  2  2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/1f6001292607457.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2qxzl1292607457.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/rcomp/tmp/3qxzl1292607457.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/rcomp/tmp/406y61292607457.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/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5wgex1292607457.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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$time.series[i,'remainder'])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6iyck1292607457.tab") 
> postscript(file="/var/www/html/rcomp/tmp/7iyck1292607457.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> myresid <- m$time.series[!is.na(m$time.series[,'remainder']),'remainder']
> hist(as.numeric(myresid), main='Residual Histogram', xlab='Residual Value')
> dev.off()
null device 
          1 
> try(system("convert tmp/1f6001292607457.ps tmp/1f6001292607457.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qxzl1292607457.ps tmp/2qxzl1292607457.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qxzl1292607457.ps tmp/3qxzl1292607457.png",intern=TRUE))
character(0)
> try(system("convert tmp/406y61292607457.ps tmp/406y61292607457.png",intern=TRUE))
character(0)
> try(system("convert tmp/7iyck1292607457.ps tmp/7iyck1292607457.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.074   0.756   2.723