workshop 9

*The author of this computation has been verified*

R Software Module: /rwasp_structuraltimeseries.wasp (opens new window with default values)

Title produced by software: Structural Time Series Models

Date of computation: Fri, 04 Dec 2009 04:56:14 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul.htm/, Retrieved Fri, 04 Dec 2009 12:57:29 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul.htm/}, year = {2009}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

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

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 0.6348 0.6348 0 0 0 2 0.634 0.634043775797653 -4.14019524637114e-05 -4.37757976527463e-05 -0.0565668498210342 3 0.62915 0.629298612086866 -6.71087687042004e-05 -0.000148612086866151 -0.586282872673047 4 0.62168 0.62187555040857 -9.54878514834116e-05 -0.000195550408570217 -0.916754315403155 5 0.61328 0.61350953878865 -0.000129179058897638 -0.000229538788649658 -1.03071856535967 6 0.6089 0.609073231484365 -0.000146714463847507 -0.000173231484365154 -0.536774383662716 7 0.60857 0.608696633837391 -0.000147646354980016 -0.000126633837391283 -0.0286488862045854 8 0.62672 0.62648368734009 -7.52387586440856e-05 0.000236312659910695 2.23507033236324 9 0.62291 0.623158572386925 -8.83067050178318e-05 -0.000248572386925168 -0.405005076359817 10 0.62393 0.623980071198226 -8.46629737372267e-05 -5.00711982260674e-05 0.113380616132610 11 0.61838 0.618583019749126 -0.000105853988011067 -0.000203019749126295 -0.662028516588124 12 0.62012 0.620159255051431 -9.91708255689625e-05 -3.92550514314409e-05 0.209619928023016 13 0.61659 0.617003162246681 2.92164355971801e-05 -0.000413162246681057 -0.458181136186446 14 0.6116 0.61172367305957 -9.62159322930973e-05 -0.000123673059570553 -0.565838730284064 15 0.61573 0.615638075615706 -8.12126883100111e-05 9.19243842942786e-05 0.499172265384509 16 0.61407 0.61422240380813 -8.35026903415249e-05 -0.000152403808130171 -0.166136859688344 17 0.62823 0.627848756999033 -5.70994857941775e-05 0.000381243000967266 1.70679881994831 18 0.64405 0.643632160286069 -2.59968424773669e-05 0.000417839713931348 1.97205033985364 19 0.6387 0.639348957373977 -3.43360630986668e-05 -0.000648957373976545 -0.529996744075801 20 0.63633 0.636063640363847 -4.06895915146999e-05 0.000266359636152796 -0.404726978093259 21 0.63059 0.630973264012296 -5.05368691862032e-05 -0.000383264012296115 -0.628653264124264 22 0.62994 0.629839786313649 -5.26512621167694e-05 0.000100213686350915 -0.134819617225985 23 0.63709 0.637024948473746 -3.78276911356679e-05 6.50515262541327e-05 0.901158016531734 24 0.64217 0.642014441243823 -3.09817630615673e-05 0.000155558756176972 0.625615995978485 25 0.65711 0.654008914474841 -0.000257347836812689 0.00310108552515894 1.63678159256294 26 0.66977 0.66961027501545 -2.56648881213365e-05 0.000159724984549867 1.80766020185603 27 0.68255 0.681808762090737 1.67866286643057e-05 0.000741237909263325 1.52002415379452 28 0.68902 0.689203908063036 2.54321665369694e-05 -0.000183908063036399 0.918347673317461 29 0.71322 0.712339956891185 5.54116653666675e-05 0.000880043108814982 2.87629889279836 30 0.70224 0.702436320161195 4.17709080785731e-05 -0.000196320161195255 -1.23947832711184 31 0.70045 0.700917479398324 3.96302418008324e-05 -0.000467479398324185 -0.194229980239109 32 0.69919 0.698757247024607 3.66210427634495e-05 0.000432752975393434 -0.273789348114225 33 0.69693 0.697166002131253 3.43985842123414e-05 -0.000236002131253049 -0.202599722514456 34 0.69763 0.697571634211625 3.49139008352257e-05 5.83657883744542e-05 0.0462037325089274 35 0.69278 0.69287664973795 2.77410337120586e-05 -9.66497379507568e-05 -0.588777664628847 36 0.70196 0.701643900096179 3.06730087737229e-05 0.000316099903821047 1.08709314853119 37 0.69215 0.693646465037395 0.000123725102927740 -0.00149646503739542 -1.05565262408303 38 0.6769 0.677774149404473 -4.01267637211755e-05 -0.000874149404472806 -1.87796195030779 39 0.67124 0.670808719195376 -6.3736237328819e-05 0.000431280804623693 -0.86034447248294 40 0.66532 0.666796169630104 -6.77111726352793e-05 -0.00147616963010449 -0.491449036653395 41 0.67157 0.670140900869694 -6.43008226161582e-05 0.00142909913030592 0.424652272371464 42 0.66428 0.664879176953151 -6.99999802085563e-05 -0.000599176953150763 -0.646772973962655 43 0.66576 0.666111268803962 -6.85552083535888e-05 -0.000351268803962295 0.162033934744073 44 0.66942 0.668880849640045 -6.5417368908221e-05 0.000539150359955356 0.353180905761929 45 0.6813 0.681053688418615 -5.18824598589055e-05 0.000246311581384771 1.52294352820467 46 0.69144 0.69083976047504 -4.05243196551376e-05 0.000600239524960272 1.22430799130474 47 0.69862 0.699022640706795 -3.02642941436875e-05 -0.000402640706794936 1.02354165671426 48 0.695 0.694839967600024 -2.92302417333965e-05 0.000160032399975887 -0.51647898515867 49 0.69867 0.69773954557356 -5.26236211033291e-05 0.000930454426440282 0.378248018047598 50 0.68968 0.690621020073305 -0.000106723052281708 -0.000941020073305363 -0.843503353862849 51 0.69233 0.691554537969385 -0.000103232713822252 0.000775462030614695 0.129121422277859 52 0.68293 0.685073982292132 -0.000109541623784688 -0.00214398229213170 -0.793672419050343 53 0.68399 0.682372306989461 -0.000111703352653755 0.00161769301053887 -0.32255152923866 54 0.66895 0.67026899634846 -0.000122950053434896 -0.00131899634845996 -1.49214259168660 55 0.68756 0.686706940139958 -0.000106968863347186 0.000853059860041534 2.06070863365380 56 0.68527 0.685565481695672 -0.000107964890983330 -0.000295481695672165 -0.128723757344901 57 0.6776 0.678307580003903 -0.000114901390153306 -0.000707580003903233 -0.889688491672784 58 0.68137 0.681022276578974 -0.000111959441727345 0.000347723421025753 0.352123305817686 59 0.67933 0.679700968497827 -0.000113231299108571 -0.00037096849782673 -0.150509747255192 60 0.67922 0.67925632172993 -0.000113030941972195 -3.63217299293497e-05 -0.0412272507041686

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/1gknz1259927771.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/1gknz1259927771.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/2ptww1259927771.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/2ptww1259927771.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/36uws1259927771.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/36uws1259927771.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/4lo1y1259927771.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/4lo1y1259927771.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/5asjo1259927771.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599278428529s1fvb4mxlul/5asjo1259927771.ps (open in new window)

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) nx <- length(x) x <- ts(x,frequency=par1) m <- StructTS(x,type='BSM') m$coef m$fitted m$resid mylevel <- as.numeric(m$fitted[,'level']) myslope <- as.numeric(m$fitted[,'slope']) myseas <- as.numeric(m$fitted[,'sea']) myresid <- as.numeric(m$resid) myfit <- mylevel+myseas mylagmax <- nx/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level') acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(mylevel,main='Level') spectrum(myseas,main='Seasonal') spectrum(myresid,main='Standardized Residals') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(mylevel,main='Level') cpgram(myseas,main='Seasonal') cpgram(myresid,main='Standardized Residals') par(op) dev.off() bitmap(file='test1.png') plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b') grid() dev.off() bitmap(file='test5.png') 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() load(file='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='mytable.tab')

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This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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