ws 8

*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: Sun, 12 Dec 2010 19:13:20 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg.htm/, Retrieved Sun, 12 Dec 2010 20:11:11 +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/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg.htm/}, year = {2010}, } @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 = {2010}, 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 «

1.3031 1.3241 1.2961 1.2865 1.2305 1.2101 1.2125 1.2350 1.2014 1.1992 1.1791 1.1832 1.2159 1.1922 1.2114 1.2614 1.2812 1.2786 1.2772 1.2815 1.2679 1.2765 1.3247 1.3191 1.3029 1.3234 1.3354 1.3651 1.3453 1.3534 1.3706 1.3638 1.4268 1.4485 1.4635 1.4587 1.4876 1.5189 1.5783 1.5633 1.5554 1.5757 1.5593 1.4660 1.4065 1.2759 1.2705 1.3954 1.2793 1.2694 1.3282 1.3230 1.4135 1.4042 1.4253 1.4322 1.4632 1.4713 1.5016 1.4318

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 4 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 1.3031 1.3031 0 0 0 2 1.3241 1.32300800006159 0.00109199993705762 0.00109199993841378 0.284544909239405 3 1.2961 1.29512390443971 0.000976095560289192 0.00097609556028919 -0.691139502135368 4 1.2865 1.28556587307044 0.000934126929555057 0.000934126929555057 -0.251258608894471 5 1.2305 1.22979090913222 0.000709090867774892 0.000709090867774893 -1.35260712073784 6 1.2101 1.20947401578439 0.000625984215611987 0.000625984215611988 -0.501501141687857 7 1.2125 1.21186705886014 0.000632941139856673 0.000632941139856674 0.0421466676067974 8 1.235 1.23428164066636 0.000718359333637368 0.000718359333637367 0.519516656049798 9 1.2014 1.20081517513086 0.000584824869139562 0.00058482486913956 -0.81534034466468 10 1.1992 1.19862596902509 0.00057403097491129 0.00057403097491129 -0.0661627566561902 11 1.1791 1.17860579153399 0.000494208466012981 0.000494208466012981 -0.491183905484689 12 1.1832 1.18269192310579 0.000508076894207854 0.000508076894207854 0.0856688263444004 13 1.2159 1.20932887166569 -0.00059737530509003 0.00657112833430543 0.75293148809392 14 1.1922 1.19317399995478 -0.000973999974556624 -0.000973999954777134 -0.315695399333558 15 1.2114 1.21233738654445 -0.000937386544454878 -0.000937386544454879 0.47979592591895 16 1.2614 1.26224510867252 -0.000845108672518426 -0.00084510867251843 1.21144001203051 17 1.2812 1.28200777574635 -0.000807775746347255 -0.000807775746347254 0.491001863969149 18 1.2786 1.2794110108081 -0.000811010808098767 -0.000811010808098766 -0.0426244735224776 19 1.2772 1.27801207204986 -0.000812072049860374 -0.000812072049860374 -0.0140079541182102 20 1.2815 1.28230287767589 -0.000802877675891391 -0.000802877675891392 0.121580816674373 21 1.2679 1.2687258527603 -0.000825852760301605 -0.000825852760301609 -0.304355471633153 22 1.2765 1.27730896055146 -0.000808960551459083 -0.000808960551459083 0.224176530719851 23 1.3247 1.32542128799443 -0.000721287994432987 -0.00072128799443299 1.16558964720041 24 1.3191 1.31982999997995 -0.000729999979948916 -0.000729999979948914 -0.116031542813216 25 1.3029 1.29917518364635 -0.000338619668924149 0.00372481635365155 -0.523037542810113 26 1.3234 1.32335776469896 4.22352932610852e-05 4.22353010408676e-05 0.530589056506489 27 1.3354 1.33534371327902 5.62867209832501e-05 5.6286720983248e-05 0.284481271817941 28 1.3651 1.36500892018877 9.10798112281102e-05 9.10798112281042e-05 0.705239422293093 29 1.3453 1.34523223915659 6.77608434091449e-05 6.77608434091454e-05 -0.473219504090004 30 1.3534 1.35332283372445 7.716627555324e-05 7.716627555324e-05 0.191091427839903 31 1.3706 1.3705028070186 9.71929814008855e-05 9.71929814008849e-05 0.407361997632161 32 1.3638 1.36371086448693 8.91355130702872e-05 8.91355130702862e-05 -0.164088274049579 33 1.4268 1.42663745624462 0.000162543755384467 0.000162543755384465 1.49668745598011 34 1.4485 1.44831235431459 0.000187645685411225 0.000187645685411226 0.512389438658394 35 1.4635 1.46329511059617 0.000204889403829276 0.000204889403829273 0.352395333095917 36 1.4587 1.45850093023494 0.000199069765063544 0.000199069765063544 -0.119069583823409 37 1.4876 1.48595504590463 -0.000149541281504454 0.00164495409537356 0.692932912639914 38 1.5189 1.51867373912774 0.000226260866536672 0.000226260872255575 0.730900620931029 39 1.5783 1.57802232841095 0.000277671589046375 0.000277671589046374 1.40798901159727 40 1.5633 1.56303559027856 0.000264409721441423 0.000264409721441418 -0.363519394857206 41 1.5554 1.55514267129301 0.000257328706988951 0.000257328706988951 -0.194265361851859 42 1.5757 1.57542530329375 0.000274696706253584 0.000274696706253585 0.476898929435036 43 1.5593 1.55903974026049 0.000260259739510269 0.000260259739510268 -0.396760884678923 44 1.466 1.46582067474066 0.000179325259337654 0.000179325259337662 -2.22619133601994 45 1.4065 1.40637225583387 0.000127744166132186 0.000127744166132181 -1.4200222072003 46 1.2759 1.27588514680386 1.48531961446394e-05 1.485319614464e-05 -3.11056414166282 47 1.2705 1.27048981880831 1.01811916942101e-05 1.01811916942064e-05 -0.128842232932366 48 1.3954 1.39528215517216 0.000117844827841088 0.000117844827841085 2.97165750065224 49 1.2793 1.29144035896482 0.00110366899876624 -0.0121403589648204 -2.60057471451443 50 1.2694 1.26851372416855 0.000886275856451274 0.000886275831450488 -0.542525372398785 51 1.3282 1.32727381116801 0.000926188831985596 0.000926188831985596 1.37813188896661 52 1.323 1.32207803030632 0.000921969693683733 0.000921969693683727 -0.145780612842954 53 1.4135 1.41251637990711 0.000983620092890857 0.00098362009289086 2.13162597667844 54 1.4042 1.40322345254814 0.000976547451856984 0.000976547451856987 -0.244712200534846 55 1.4253 1.4243096219966 0.000990378003396628 0.000990378003396627 0.478864006604029 56 1.4322 1.4312055631903 0.000994436809701294 0.000994436809701295 0.140627257097516 57 1.4632 1.46218496911816 0.00101503088183856 0.00101503088183856 0.714022156876081 58 1.4713 1.47028010974292 0.0010198902570771 0.0010198902570771 0.168596272983934 59 1.5016 1.50056004112767 0.00103995887233332 0.00103995887233332 0.696759358298355 60 1.4318 1.4308085616473 0.00099143835269702 0.000991438352697016 -1.68573192903972

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/1sksi1292181195.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/1sksi1292181195.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/23bsl1292181195.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/23bsl1292181195.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/3e29o1292181195.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/3e29o1292181195.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/4e29o1292181195.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/4e29o1292181195.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/57c8r1292181195.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t1292181070ugmwoeqc9d0vwmg/57c8r1292181195.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 1 ;

Parameters (R input):

par1 = 12 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 1 ;

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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