R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(46,62,66,59,58,61,41,27,58,70,49,59,44,36,72,45,56,54,53,35,61,52,47,51,52,63,74,45,51,64,36,30,55,64,39,40,63,45,59,55,40,64,27,28,45,57,45,69,60,56,58,50,51,53,37,22,55,70,62,58,39,49,58,47,42,62,39,40,72,70,54,65)
> par1 = '12'
> par1 <- as.numeric(par1)
> nx <- length(x)
> x <- ts(x,frequency=par1)
> m <- StructTS(x,type='BSM')
> m$coef
    level     slope      seas   epsilon 
 1.489593  0.000000 12.250964 73.216610 
> m$fitted
         level      slope         sea
Jan 1 46.00000 0.00000000   0.0000000
Feb 1 47.91108 0.45772406   3.2729431
Mar 1 52.21815 1.23550515   3.1103923
Apr 1 54.80852 1.45917164   0.8854140
May 1 56.45329 1.48495789   1.0975000
Jun 1 58.30254 1.52861925   1.7877365
Jul 1 55.50976 1.07340991  -3.2048306
Aug 1 49.86601 0.44240453  -4.3679817
Sep 1 51.13490 0.51245455   4.4694784
Oct 1 55.14969 0.78286216   4.1917807
Nov 1 54.83126 0.70478025  -2.3247826
Dec 1 55.92697 0.73040832   1.7757929
Jan 2 56.33223 0.73655616 -10.1265569
Feb 2 53.31611 0.55136779  -4.8504936
Mar 2 56.14621 0.67845888   9.1817277
Apr 2 55.05810 0.58285246  -4.7436035
May 2 55.42482 0.57181165   1.2602135
Jun 2 55.12172 0.52978632   1.7912389
Jul 2 55.20652 0.50964904  -0.6614253
Aug 2 53.29288 0.40599357  -9.5756859
Sep 2 54.04462 0.42001787   5.6738770
Oct 2 53.51617 0.38345050   2.0913550
Nov 2 53.18381 0.35732989  -3.3930765
Dec 2 52.75764 0.33182114   1.4235162
Jan 3 53.39369 0.33446682  -2.9124829
Feb 3 55.75063 0.38638317  -1.0805012
Mar 3 57.49724 0.42979444  11.3354837
Apr 3 57.00921 0.39955525  -8.5554331
May 3 56.16349 0.35939414  -0.4099527
Jun 3 57.00852 0.37447902   5.1008697
Jul 3 54.46466 0.28752175  -6.8832293
Aug 3 52.37783 0.21965629 -12.7911150
Sep 3 51.68268 0.19456135   7.0681779
Oct 3 52.89498 0.22128093   6.8713067
Nov 3 51.85391 0.19013468  -7.5133996
Dec 3 50.31703 0.15340041  -2.7811444
Jan 4 52.13367 0.17285145   2.9916185
Feb 4 51.87769 0.16516410  -4.9898494
Mar 4 51.30819 0.14894084  10.7700741
Apr 4 52.71549 0.17850630  -2.9123357
May 4 51.46081 0.14474089  -5.5262808
Jun 4 51.91140 0.15179678  10.8107602
Jul 4 49.56963 0.09598691 -12.0404445
Aug 4 48.13984 0.06298116 -13.6291438
Sep 4 46.77356 0.03319338   4.3873025
Oct 4 46.77650 0.03259078  10.3552839
Nov 4 47.29314 0.04157414  -4.4294779
Dec 4 50.41295 0.09094614   4.7042797
Jan 5 51.59054 0.10364592   3.3274222
Feb 5 52.92268 0.12120217  -2.4892211
Mar 5 52.66961 0.11488016   6.9761001
Apr 5 52.58734 0.11130456  -1.7314572
May 5 53.05285 0.11784195  -3.5885917
Jun 5 51.55487 0.08828470   8.4802755
Jul 5 50.88449 0.07470688 -10.5601552
Aug 5 48.87964 0.03855472 -17.7022885
Sep 5 48.85522 0.03749824   6.4247831
Oct 5 50.27520 0.05962355  13.5276374
Nov 5 52.78821 0.09614114  -1.8991991
Dec 5 53.47354 0.10387366   1.8186635
Jan 6 51.83046 0.08474324  -4.6598879
Feb 6 51.56944 0.08054891  -0.9766265
Mar 6 51.45750 0.07790217   7.4130045
Apr 6 51.12403 0.07184414  -2.2821231
May 6 50.23679 0.05736287  -3.9530552
Jun 6 50.36814 0.05847914  11.3007753
Jul 6 50.11049 0.05378350  -9.6901483
Aug 6 51.05559 0.06669323 -15.0807023
Sep 6 53.13715 0.09489685   9.7118707
Oct 6 54.17714 0.10752073  11.5025732
Nov 6 54.63671 0.11191017  -2.2587760
Dec 6 55.54991 0.12092731   5.7212848
> m$resid
          Jan         Feb         Mar         Apr         May         Jun
1  0.00000000  1.53740451  1.66338386  0.52467341  0.07120277  0.14326850
2 -0.32951888 -1.97251267  1.08290458 -0.86275851 -0.11064540 -0.46807717
3  0.23801240  1.33111768  0.83617466 -0.56070375 -0.77134109  0.30631990
4  1.25745344 -0.30371123 -0.49870628  0.84437967 -0.96476055  0.20764619
5  0.81793913  0.89873111 -0.26678153 -0.13905229  0.24969376 -1.14380920
6 -1.31979261 -0.25765731 -0.14115327 -0.29914876 -0.69622575  0.05381792
          Jul         Aug         Sep         Oct         Nov         Dec
1 -1.76638756 -2.86761758  0.36866959  1.62955341 -0.53300378  0.19619183
2 -0.24720098 -1.38968831  0.20369162 -0.57195297 -0.44129416 -0.50031233
3 -1.87338611 -1.54838802 -0.60498508  0.68191892 -0.85853993 -1.20701560
4 -1.70966313 -1.05627182 -0.99862596 -0.02133906  0.34539382  2.23926443
5 -0.54028242 -1.49072514 -0.04545185  1.00512116  1.80000346  0.43800169
6 -0.23083307  0.65391133  1.48588762  0.70103346  0.26297524  0.60390689
> mylevel <- as.numeric(m$fitted[,'level'])
> myslope <- as.numeric(m$fitted[,'slope'])
> myseas <- as.numeric(m$fitted[,'sea'])
> myresid <- as.numeric(m$resid)
> myfit <- mylevel+myseas
> mylagmax <- nx/2
> postscript(file="/var/fisher/rcomp/tmp/1ufo11353760598.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
> acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
> acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/2q2nm1353760598.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(mylevel,main='Level')
> spectrum(myseas,main='Seasonal')
> spectrum(myresid,main='Standardized Residals')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/3vawp1353760598.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(mylevel,main='Level')
> cpgram(myseas,main='Seasonal')
> cpgram(myresid,main='Standardized Residals')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/4h1ps1353760598.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/5y1c51353760598.ps",horizontal=F,onefile=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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/60gbv1353760598.tab") 
> 
> try(system("convert tmp/1ufo11353760598.ps tmp/1ufo11353760598.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q2nm1353760598.ps tmp/2q2nm1353760598.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vawp1353760598.ps tmp/3vawp1353760598.png",intern=TRUE))
character(0)
> try(system("convert tmp/4h1ps1353760598.ps tmp/4h1ps1353760598.png",intern=TRUE))
character(0)
> try(system("convert tmp/5y1c51353760598.ps tmp/5y1c51353760598.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.564   0.688   4.261