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(0.6348,0.634,0.62915,0.62168,0.61328,0.6089,0.60857,0.62672,0.62291,0.62393,0.61838,0.62012,0.61659,0.6116,0.61573,0.61407,0.62823,0.64405,0.6387,0.63633,0.63059,0.62994,0.63709,0.64217,0.65711,0.66977,0.68255,0.68902,0.71322,0.70224,0.70045,0.69919,0.69693,0.69763,0.69278,0.70196,0.69215,0.6769,0.67124,0.66532,0.67157,0.66428,0.66576,0.66942,0.6813,0.69144,0.69862,0.695,0.69867,0.68968,0.69233,0.68293,0.68399,0.66895,0.68756,0.68527,0.6776,0.68137,0.67933,0.67922)
> 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 
6.464211e-05 0.000000e+00 3.815336e-07 0.000000e+00 
> m$fitted
          level         slope           sea
Jan 1 0.6348000  0.000000e+00  0.000000e+00
Feb 1 0.6340438 -4.140195e-05 -4.377580e-05
Mar 1 0.6292986 -6.710877e-05 -1.486121e-04
Apr 1 0.6218756 -9.548785e-05 -1.955504e-04
May 1 0.6135095 -1.291791e-04 -2.295388e-04
Jun 1 0.6090732 -1.467145e-04 -1.732315e-04
Jul 1 0.6086966 -1.476464e-04 -1.266338e-04
Aug 1 0.6264837 -7.523876e-05  2.363127e-04
Sep 1 0.6231586 -8.830671e-05 -2.485724e-04
Oct 1 0.6239801 -8.466297e-05 -5.007120e-05
Nov 1 0.6185830 -1.058540e-04 -2.030197e-04
Dec 1 0.6201593 -9.917083e-05 -3.925505e-05
Jan 2 0.6170032  2.921644e-05 -4.131622e-04
Feb 2 0.6117237 -9.621593e-05 -1.236731e-04
Mar 2 0.6156381 -8.121269e-05  9.192438e-05
Apr 2 0.6142224 -8.350269e-05 -1.524038e-04
May 2 0.6278488 -5.709949e-05  3.812430e-04
Jun 2 0.6436322 -2.599684e-05  4.178397e-04
Jul 2 0.6393490 -3.433606e-05 -6.489574e-04
Aug 2 0.6360636 -4.068959e-05  2.663596e-04
Sep 2 0.6309733 -5.053687e-05 -3.832640e-04
Oct 2 0.6298398 -5.265126e-05  1.002137e-04
Nov 2 0.6370249 -3.782769e-05  6.505153e-05
Dec 2 0.6420144 -3.098176e-05  1.555588e-04
Jan 3 0.6540089 -2.573478e-04  3.101086e-03
Feb 3 0.6696103 -2.566489e-05  1.597250e-04
Mar 3 0.6818088  1.678663e-05  7.412379e-04
Apr 3 0.6892039  2.543217e-05 -1.839081e-04
May 3 0.7123400  5.541167e-05  8.800431e-04
Jun 3 0.7024363  4.177091e-05 -1.963202e-04
Jul 3 0.7009175  3.963024e-05 -4.674794e-04
Aug 3 0.6987572  3.662104e-05  4.327530e-04
Sep 3 0.6971660  3.439858e-05 -2.360021e-04
Oct 3 0.6975716  3.491390e-05  5.836579e-05
Nov 3 0.6928766  2.774103e-05 -9.664974e-05
Dec 3 0.7016439  3.067301e-05  3.160999e-04
Jan 4 0.6936465  1.237251e-04 -1.496465e-03
Feb 4 0.6777741 -4.012676e-05 -8.741494e-04
Mar 4 0.6708087 -6.373624e-05  4.312808e-04
Apr 4 0.6667962 -6.771117e-05 -1.476170e-03
May 4 0.6701409 -6.430082e-05  1.429099e-03
Jun 4 0.6648792 -6.999998e-05 -5.991770e-04
Jul 4 0.6661113 -6.855521e-05 -3.512688e-04
Aug 4 0.6688808 -6.541737e-05  5.391504e-04
Sep 4 0.6810537 -5.188246e-05  2.463116e-04
Oct 4 0.6908398 -4.052432e-05  6.002395e-04
Nov 4 0.6990226 -3.026429e-05 -4.026407e-04
Dec 4 0.6948400 -2.923024e-05  1.600324e-04
Jan 5 0.6977395 -5.262362e-05  9.304544e-04
Feb 5 0.6906210 -1.067231e-04 -9.410201e-04
Mar 5 0.6915545 -1.032327e-04  7.754620e-04
Apr 5 0.6850740 -1.095416e-04 -2.143982e-03
May 5 0.6823723 -1.117034e-04  1.617693e-03
Jun 5 0.6702690 -1.229501e-04 -1.318996e-03
Jul 5 0.6867069 -1.069689e-04  8.530599e-04
Aug 5 0.6855655 -1.079649e-04 -2.954817e-04
Sep 5 0.6783076 -1.149014e-04 -7.075800e-04
Oct 5 0.6810223 -1.119594e-04  3.477234e-04
Nov 5 0.6797010 -1.132313e-04 -3.709685e-04
Dec 5 0.6792563 -1.130309e-04 -3.632173e-05
> m$resid
          Jan         Feb         Mar         Apr         May         Jun
1  0.00000000 -0.05656685 -0.58628287 -0.91675432 -1.03071857 -0.53677438
2 -0.45818114 -0.56583873  0.49917227 -0.16613686  1.70679882  1.97205034
3  1.63678159  1.80766020  1.52002415  0.91834767  2.87629889 -1.23947833
4 -1.05565262 -1.87796195 -0.86034447 -0.49144904  0.42465227 -0.64677297
5  0.37824802 -0.84350335  0.12912142 -0.79367242 -0.32255153 -1.49214259
          Jul         Aug         Sep         Oct         Nov         Dec
1 -0.02864889  2.23507033 -0.40500508  0.11338062 -0.66202852  0.20961993
2 -0.52999674 -0.40472698 -0.62865326 -0.13481962  0.90115802  0.62561600
3 -0.19422998 -0.27378935 -0.20259972  0.04620373 -0.58877766  1.08709315
4  0.16203393  0.35318091  1.52294353  1.22430799  1.02354166 -0.51647899
5  2.06070863 -0.12872376 -0.88968849  0.35212331 -0.15050975 -0.04122725
> 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/1gknz1259927771.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/2ptww1259927771.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/36uws1259927771.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/4lo1y1259927771.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5asjo1259927771.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> hist(m$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/6gh981259927771.tab") 
> system("convert tmp/1gknz1259927771.ps tmp/1gknz1259927771.png")
> system("convert tmp/2ptww1259927771.ps tmp/2ptww1259927771.png")
> system("convert tmp/36uws1259927771.ps tmp/36uws1259927771.png")
> system("convert tmp/4lo1y1259927771.ps tmp/4lo1y1259927771.png")
> system("convert tmp/5asjo1259927771.ps tmp/5asjo1259927771.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.499   0.787   2.857