R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-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(3440,2678,2981,2260,2844,2546,2456,2295,2379,2479,2057,2280,2351,2276,2548,2311,2201,2725,2408,2139,1898,2539,2070,2063,2565,2442,2194,2798,2074,2628,2289,2154,2467,2137,1850,2075,1791,1755,2232,1952,1822,2522,2074,2366,2173,2094,1833,1858,2040,2133,2921,3252,3318,3554,2308,1621,1315,1501,1418,1657)
> 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   50.76456 2800.459  588.776669
Feb 1 -112.86959 2751.922   38.947667
Mar 1  222.49589 2703.385   55.119045
Apr 1  185.05107 2658.058 -583.108578
May 1  145.40567 2612.730   85.864383
Jun 1  505.60712 2567.152 -526.759467
Jul 1   34.60842 2521.575 -100.183157
Aug 1 -143.26982 2477.364  -39.094227
Sep 1 -197.74816 2433.153  143.594810
Oct 1  -84.97671 2412.768  151.208677
Nov 1 -380.20521 2392.383   44.822495
Dec 1 -224.86335 2375.940  128.923540
Jan 2   50.76456 2359.497  -59.261470
Feb 2 -112.86959 2340.136   48.733650
Mar 2  222.49589 2320.775    4.729151
Apr 2  185.05107 2308.352 -182.402620
May 2  145.40567 2295.928 -240.333809
Jun 2  505.60712 2297.496  -78.102848
Jul 2   34.60842 2299.063   74.328272
Aug 2 -143.26982 2309.209  -26.939253
Sep 2 -197.74816 2319.355 -223.606672
Oct 2  -84.97671 2326.641  297.335341
Nov 2 -380.20521 2333.928  116.277305
Dec 2 -224.86335 2331.590  -43.726377
Jan 3   50.76456 2329.252  184.983885
Feb 3 -112.86959 2325.160  229.709727
Mar 3  222.49589 2321.068 -349.564051
Apr 3  185.05107 2313.931  299.017775
May 3  145.40567 2306.794 -378.199816
Jun 3  505.60712 2285.664 -163.271005
Jul 3   34.60842 2264.534  -10.142033
Aug 3 -143.26982 2232.893   64.376656
Sep 3 -197.74816 2201.253  463.495452
Oct 3  -84.97671 2167.006   54.970493
Nov 3 -380.20521 2132.760   97.445486
Dec 3 -224.86335 2103.387  196.476784
Jan 4   50.76456 2074.013 -333.777974
Feb 4 -112.86959 2057.577 -189.707055
Mar 4  222.49589 2041.140  -31.635756
Apr 4  185.05107 2040.662 -273.712836
May 4  145.40567 2040.184 -363.589334
Jun 4  505.60712 2054.306  -37.913507
Jul 4   34.60842 2068.429  -29.037519
Aug 4 -143.26982 2108.742  400.528150
Sep 4 -197.74816 2149.054  221.693925
Oct 4  -84.97671 2223.220  -44.243780
Nov 4 -380.20521 2297.387  -84.181535
Dec 4 -224.86335 2361.068 -278.204729
Jan 5   50.76456 2424.749 -435.513978
Feb 5 -112.86959 2425.841 -179.971326
Mar 5  222.49589 2426.932  271.571707
Apr 5  185.05107 2359.467  707.481616
May 5  145.40567 2292.002  880.592109
Jun 5  505.60712 2234.846  813.546720
Jul 5   34.60842 2177.690   95.701491
Aug 5 -143.26982 2112.921 -348.650943
Sep 5 -197.74816 2048.151 -535.403271
Oct 5  -84.97671 1970.149 -384.171975
Nov 5 -380.20521 1892.146  -93.940728
Dec 5 -224.86335 1805.719   76.143909
> 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$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1bfxz1322577404.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2pq261322577404.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/wessaorg/rcomp/tmp/3qnit1322577404.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/wessaorg/rcomp/tmp/4bbe51322577404.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5xl0e1322577404.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/wessaorg/rcomp/tmp/60xol1322577404.tab") 
> 
> try(system("convert tmp/1bfxz1322577404.ps tmp/1bfxz1322577404.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pq261322577404.ps tmp/2pq261322577404.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qnit1322577404.ps tmp/3qnit1322577404.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bbe51322577404.ps tmp/4bbe51322577404.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.272   0.205   1.495