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(25.6,23.7,22,21.3,20.7,20.4,20.3,20.4,19.8,19.5,23.1,23.5,23.5,22.9,21.9,21.5,20.5,20.2,19.4,19.2,18.8,18.8,22.6,23.3,23,21.4,19.9,18.8,18.6,18.4,18.6,19.9,19.2,18.4,21.1,20.5,19.1,18.1,17,17.1,17.4,16.8,15.3,14.3,13.4,15.3,22.1,23.7,22.2,19.5,16.6,17.3,19.8,21.2,21.5,20.6,19.1,19.6,23.5,24)
> par1 = '12'
> #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> nx <- length(x)
> x <- ts(x,frequency=par1)
> m <- StructTS(x,type='BSM')
> m$coef
     level      slope       seas    epsilon 
0.00000000 1.66211280 0.04538702 0.00000000 
> m$fitted
         level       slope          sea
Jan 1 25.60000  0.00000000  0.000000000
Feb 1 23.77483 -1.83135418 -0.074830133
Mar 1 21.94654 -1.82858782  0.053462799
Apr 1 21.21478 -0.84154378  0.085216303
May 1 20.69602 -0.55166561  0.003983011
Jun 1 20.38645 -0.33403950  0.013550389
Jul 1 20.28548 -0.12452624  0.014524826
Aug 1 20.38591  0.07769222  0.014087216
Sep 1 19.85008 -0.47379594 -0.050081049
Oct 1 19.47802 -0.38235053  0.021983579
Nov 1 22.81508  2.96100191  0.284921352
Dec 1 23.73150  1.12314014 -0.231495058
Jan 2 23.56224 -0.03776020 -0.062242560
Feb 2 22.95220 -0.55264297 -0.052195525
Mar 2 21.97070 -0.92250994 -0.070696995
Apr 2 21.39001 -0.62534426  0.109988182
May 2 20.53079 -0.82768352 -0.030792747
Jun 2 20.15890 -0.43302202  0.041100529
Jul 2 19.48880 -0.63836024 -0.088795470
Aug 2 19.06576 -0.45186958  0.134236522
Sep 2 18.68051 -0.39417753  0.119489774
Oct 2 19.16574  0.36742721 -0.365740694
Nov 2 21.94500  2.45623756  0.655004993
Dec 2 23.56284  1.73025116 -0.262837195
Jan 3 23.22443 -0.06020661 -0.224427642
Feb 3 21.52270 -1.48276851 -0.122704000
Mar 3 19.98500 -1.52962625 -0.085004200
Apr 3 18.60685 -1.39975381  0.193146908
May 3 18.56381 -0.23992177  0.036187814
Jun 3 18.34563 -0.22133518  0.054366903
Jul 3 18.66350  0.23979916 -0.063499977
Aug 3 19.61319  0.84692371  0.286812971
Sep 3 19.20943 -0.22267291 -0.009426478
Oct 3 19.12906 -0.10096761 -0.729063401
Nov 3 20.32601  1.00901148  0.773991175
Dec 3 20.65566  0.42819304 -0.155655645
Jan 4 19.29642 -1.09994836 -0.196416181
Feb 4 18.17098 -1.12174324 -0.070975982
Mar 4 17.03529 -1.13358184 -0.035285408
Apr 4 16.96660 -0.22712674  0.133403852
May 4 17.27576  0.22880932  0.124235283
Jun 4 16.89446 -0.28956042 -0.094463586
Jul 4 15.62145 -1.12550081 -0.321450621
Aug 4 13.84434 -1.67943220  0.455663510
Sep 4 13.25433 -0.75332375  0.145665510
Oct 4 15.93589  2.16659309 -0.635891529
Nov 4 21.04003  4.66352660  1.059969672
Dec 4 23.83027  3.07172723 -0.130267180
Jan 5 22.80685 -0.40898808 -0.606854071
Feb 5 19.76121 -2.64881609 -0.261205510
Mar 5 16.78389 -2.92676322 -0.183892307
Apr 5 16.96305 -0.29435784  0.336945655
May 5 19.38608  2.00791195  0.413920460
Jun 5 21.19058  1.83571274  0.009418815
Jul 5 21.71836  0.72811105 -0.218364389
Aug 5 20.28214 -1.10503089  0.317863563
Sep 5 19.34449 -0.96325943 -0.244488827
Oct 5 20.62826  0.93990691 -1.028264802
Nov 5 22.34596  1.59857481  1.154037356
Dec 5 23.68239  1.37663438  0.317609240
> m$resid
          Jan         Feb         Mar         Apr         May         Jun
1  0.00000000 -1.44810168  0.00223916  0.76249970  0.22494204  0.16880316
2 -0.90134729 -0.40294975 -0.29027438  0.23047893 -0.15688674  0.30617068
3 -1.39058360 -1.10542355 -0.03646650  0.10089423  0.89886472  0.01441946
4 -1.18680540 -0.01690638 -0.00919402  0.70421780  0.35337994 -0.40210088
5 -2.70245694 -1.73680562 -0.21571908  2.04447234  1.78481278 -0.13355854
          Jul         Aug         Sep         Oct         Nov         Dec
1  0.16251091  0.15685219 -0.42776570  0.07093028  2.59329494 -1.42555047
2 -0.15926996  0.14465329  0.04474924  0.59074425  1.62020863 -0.56312255
3  0.35768210  0.47091929 -0.82964081  0.09440184  0.86096764 -0.45054746
4 -0.64842930 -0.42965604  0.71834434  2.26487758  1.93675299 -1.23489682
5 -0.85917671 -1.42187340  0.10996645  1.47622698  0.51089548 -0.17219061
> mylevel <- as.numeric(m$fitted[,'level'])
> myslope <- as.numeric(m$fitted[,'slope'])
> myseas <- as.numeric(m$fitted[,'sea'])
> myresid <- as.numeric(m$resid)
> myfit <- mylevel+myseas
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/1u5ry1261432287.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(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
> acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
> acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2mktb1261432287.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(mylevel,main='Level')
> spectrum(myseas,main='Seasonal')
> spectrum(myresid,main='Standardized Residals')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3l2zx1261432287.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(mylevel,main='Level')
> cpgram(myseas,main='Seasonal')
> cpgram(myresid,main='Standardized Residals')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/42ndh1261432287.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5lnty1261432287.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> hist(m$resid,main='Residual Histogram')
> plot(density(m$resid),main='Residual Kernel Density')
> qqnorm(m$resid,main='Residual Normal QQ Plot')
> qqline(m$resid)
> plot(m$resid^2, myfit^2,main='Sq.Resid vs. Sq.Fit',xlab='Squared residuals',ylab='Squared Fit')
> 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,'Structural Time Series Model',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,'Level',header=TRUE)
> a<-table.element(a,'Slope',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Stand. Residuals',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,mylevel[i])
+ a<-table.element(a,myslope[i])
+ a<-table.element(a,myseas[i])
+ a<-table.element(a,myresid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6ctqb1261432287.tab") 
> 
> try(system("convert tmp/1u5ry1261432287.ps tmp/1u5ry1261432287.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mktb1261432287.ps tmp/2mktb1261432287.png",intern=TRUE))
character(0)
> try(system("convert tmp/3l2zx1261432287.ps tmp/3l2zx1261432287.png",intern=TRUE))
character(0)
> try(system("convert tmp/42ndh1261432287.ps tmp/42ndh1261432287.png",intern=TRUE))
character(0)
> try(system("convert tmp/5lnty1261432287.ps tmp/5lnty1261432287.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.339   0.809   2.373