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)

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> x <- c(101.76,102.37,102.38,102.86,102.87,102.92,102.95,103.02,104.08,104.16,104.24,104.33,104.73,104.86,105.03,105.62,105.63,105.63,105.94,106.61,107.69,107.78,107.93,108.48,108.14,108.48,108.48,108.89,108.93,109.21,109.47,109.80,111.73,111.85,112.12,112.15,112.17,112.67,112.80,113.44,113.53,114.53,114.51,115.05,116.67,117.07,116.92,117.00,117.02,117.35,117.36,117.82,117.88,118.24,118.50,118.80,119.76,120.09)
> 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 
0.078186056 0.002137863 0.006093098 0.000000000 
> m$fitted
         level      slope          sea
Jan 1 101.7600 0.00000000  0.000000000
Feb 1 102.3175 0.03471860  0.052527282
Mar 1 102.3631 0.03537100  0.016903297
Apr 1 102.7660 0.06182677  0.093987862
May 1 102.8565 0.06439382  0.013474006
Jun 1 102.8951 0.06170220  0.024855807
Jul 1 102.9233 0.05780779  0.026733595
Aug 1 102.9864 0.05846742  0.033639220
Sep 1 103.9064 0.17168656  0.173615991
Oct 1 104.1624 0.18317896 -0.002351654
Nov 1 104.2311 0.16715974  0.008888937
Dec 1 104.3064 0.15405268  0.023597775
Jan 2 104.8605 0.20711741 -0.130469594
Feb 2 104.8566 0.17623744  0.003363404
Mar 2 105.0690 0.18151456 -0.039025951
Apr 2 105.4947 0.21728865  0.125267205
May 2 105.6576 0.20928709 -0.027563137
Jun 2 105.6520 0.17763983 -0.022031425
Jul 2 105.8812 0.18524587  0.058808507
Aug 2 106.5981 0.26384910  0.011924597
Sep 2 107.4500 0.35088914  0.239995875
Oct 2 107.8200 0.35372170 -0.040014813
Nov 2 107.9715 0.32375640 -0.041538110
Dec 2 108.4742 0.35019604  0.005820055
Jan 3 108.3698 0.28346985 -0.229835685
Feb 3 108.5026 0.26120384 -0.022559420
Mar 3 108.5958 0.23651896 -0.115840947
Apr 3 108.7541 0.22496301  0.135922516
May 3 108.9060 0.21416193  0.023991444
Jun 3 109.1951 0.22523895  0.014932550
Jul 3 109.4916 0.23578814 -0.021641959
Aug 3 109.8725 0.25724097 -0.072496921
Sep 3 111.2279 0.41965620  0.502063440
Oct 3 111.8671 0.45211776 -0.017074626
Nov 3 112.2490 0.44174303 -0.129011290
Dec 3 112.1890 0.36773034 -0.038971201
Jan 4 112.3902 0.34318023 -0.220198531
Feb 4 112.6631 0.33280180  0.006944535
Mar 4 112.9088 0.32000483 -0.108784345
Apr 4 113.2630 0.32504795  0.176976886
May 4 113.5193 0.31489911  0.010674793
Jun 4 114.3620 0.39283914  0.167971386
Jul 4 114.6179 0.37261819 -0.107911585
Aug 4 115.2849 0.41608041 -0.234914565
Sep 4 116.1315 0.47963653  0.538533115
Oct 4 117.0003 0.53709727  0.069684043
Nov 4 117.0856 0.47044060 -0.165593724
Dec 4 117.1084 0.40449440 -0.108378747
Jan 5 117.2707 0.36878406 -0.250661658
Feb 5 117.3729 0.32947823 -0.022915778
Mar 5 117.4977 0.29937926 -0.137660005
Apr 5 117.6493 0.27763154  0.170744600
May 5 117.9503 0.28108931 -0.070340427
Jun 5 118.0704 0.25733535  0.169612596
Jul 5 118.5967 0.29700405 -0.096688310
Aug 5 119.1029 0.32785373 -0.302877514
Sep 5 119.3481 0.31566802  0.411897415
Oct 5 119.8734 0.34657441  0.216624672
> m$resid
          Jan         Feb         Mar         Apr         May         Jun
1  0.00000000  1.21653408  0.03748073  1.26006629  0.09706146 -0.08633555
2  1.47412310 -0.61391939  0.11447027  0.78666831 -0.17480508 -0.68946249
3 -1.52703398 -0.46657340 -0.52880654 -0.25096350 -0.23353341  0.23928721
4 -0.54425958 -0.22151203 -0.27444783  0.10944001 -0.21964080  1.68370953
5 -0.78260587 -0.84439173 -0.64651014 -0.47142213  0.07488751 -0.51339088
          Jul         Aug         Sep         Oct         Nov         Dec
1 -0.11155892  0.01744955  2.82958576  0.27575522 -0.37330015 -0.29909095
2  0.16539289  1.70670020  1.88783101  0.06139018 -0.64903430  0.57327706
3  0.22800990  0.46385685  3.51250251  0.70208973 -0.22428567 -1.60540473
4 -0.43693661  0.93960182  1.37440659  1.24250556 -1.44086873 -1.43164645
5  0.85719464  0.66689515 -0.26348913  0.66816765                        
> 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/wessaorg/rcomp/tmp/1z0r11322602668.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/wessaorg/rcomp/tmp/2o1861322602668.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/wessaorg/rcomp/tmp/31l501322602668.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/wessaorg/rcomp/tmp/4afom1322602668.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/5dbcf1322602668.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> hist(m$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/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,'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/wessaorg/rcomp/tmp/60mjl1322602668.tab") 
> 
> try(system("convert tmp/1z0r11322602668.ps tmp/1z0r11322602668.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o1861322602668.ps tmp/2o1861322602668.png",intern=TRUE))
character(0)
> try(system("convert tmp/31l501322602668.ps tmp/31l501322602668.png",intern=TRUE))
character(0)
> try(system("convert tmp/4afom1322602668.ps tmp/4afom1322602668.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dbcf1322602668.ps tmp/5dbcf1322602668.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.769   0.271   2.040