WS9 Ad Hoc Forecasting Structual Time Series Models

*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 08:06:07 -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/t1259939288pkptiqcnht5im2l.htm/, Retrieved Fri, 04 Dec 2009 16:08:14 +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/t1259939288pkptiqcnht5im2l.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:

KVN WS9

Dataseries X:

» Textbox « » Textfile « » CSV «

9487 8700 9627 8947 9283 8829 9947 9628 9318 9605 8640 9214 9567 8547 9185 9470 9123 9278 10170 9434 9655 9429 8739 9552 9687 9019 9672 9206 9069 9788 10312 10105 9863 9656 9295 9946 9701 9049 10190 9706 9765 9893 9994 10433 10073 10112 9266 9820 10097 9115 10411 9678 10408 10153 10368 10581 10597 10680 9738 9556

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 9487 9487 0 0 0 2 8700 9410.66221960605 14.8108814183293 -642.752915342371 -2.62458917471795 3 9627 9348.40296095017 8.02078819678196 293.120717707555 -0.664671325135038 4 8947 9192.92784714829 -8.50367448345273 -221.564622870867 -1.26282999082043 5 9283 9172.06254172394 -9.6570099828324 113.156136112896 -0.112903261111508 6 8829 9078.49383991027 -16.3160406007255 -231.291809831184 -0.889906262034115 7 9947 9246.42952599754 -4.29398424098241 655.595539967776 2.13703771174858 8 9628 9394.1319756856 3.88784536467991 194.286715291542 1.84896929418436 9 9318 9434.3341700878 5.54722596344084 -126.118482900254 0.452657917888549 10 9605 9488.81897605408 7.52115489412555 102.760309407876 0.617558702801716 11 8640 9323.67893841986 1.14200281874054 -635.897744727849 -2.19217046498565 12 9214 9234.35550439917 -2.00605165711058 4.79386592307969 -1.15197052002735 13 9567 9230.45376913785 -2.00196394364269 337.109387507222 -0.0260403334206382 14 8547 9186.98962196303 -2.07779769166592 -627.844170684221 -0.562301320083703 15 9185 9074.75238580067 -4.15498867485569 139.693470646838 -1.37964439611391 16 9470 9172.04499784956 -0.88651791322982 273.017458044550 1.19150265866024 17 9123 9181.4710330038 -0.485173195438105 -60.9272220741548 0.119021321536663 18 9278 9308.78595960706 4.68018419285406 -61.5660556680941 1.49787747031796 19 10170 9429.39346103096 9.16153687268503 711.871907006624 1.39504374988515 20 9434 9435.2259234481 9.04431862735718 -0.376278508238181 -0.0410484120550867 21 9655 9501.92182701965 10.8372983815244 138.019082481754 0.723823830116898 22 9429 9452.06918935972 9.21038879562885 -6.9508097652243 -0.771232255723555 23 8739 9401.8911808807 7.87844906618502 -646.931275747359 -0.760751721349243 24 9552 9410.67595345954 7.89468763914617 141.078180657259 0.0116841337970853 25 9687 9395.03211584566 7.5793584161868 298.412950089261 -0.305638803709976 26 9019 9444.02942164648 8.11940645079544 -436.318683177615 0.5353335057332 27 9672 9514.830425391 9.12571451795844 140.415875604306 0.796654602451242 28 9206 9441.237803343 7.46306392857916 -213.647486248494 -1.03183614132802 29 9069 9385.90972188335 5.99446764474676 -300.778691902143 -0.774889456941147 30 9788 9491.08204404572 8.4899684483007 271.528378302055 1.22357523621751 31 10312 9554.94988822634 9.89540179112183 742.784714301401 0.687999759794703 32 10105 9698.52281611874 13.1495405034614 371.665429040215 1.67702598767539 33 9863 9741.8611219157 13.8276660028135 113.187163186165 0.382258350719207 34 9656 9735.31381633368 13.4174294774220 -73.8942293904185 -0.259921477184466 35 9295 9782.61974398682 14.0178772153166 -496.702244526805 0.434673243278042 36 9946 9811.3603065055 14.2471905854922 130.673211137978 0.189519212212617 37 9701 9751.49378209906 13.2010167130039 -30.4799533687047 -0.955296321157828 38 9049 9684.36550516303 12.0932150878748 -613.716658893921 -1.03318116150092 39 10190 9732.81401893276 12.6213954112782 447.448573649255 0.46510085549231 40 9706 9802.99465107967 13.5334303953238 -112.289974140224 0.731760978539261 41 9765 9921.08108203018 15.3286554513203 -183.688948439068 1.32326995921778 42 9893 9929.71528918419 15.2076123486711 -34.9521925049193 -0.0846274532953867 43 9994 9820.57479317663 12.9225934420333 206.216609388381 -1.57492203231377 44 10433 9843.61236940985 13.1051449576991 586.709552922766 0.128594746605431 45 10073 9880.14274997817 13.5085258476598 186.623045936273 0.299105764645484 46 10112 9964.71202891855 14.6518360874417 128.280266060680 0.910962070429564 47 9266 9950.68989886557 14.2251414897267 -676.987541670659 -0.3687439599434 48 9820 9881.33586650173 13.0701928574185 -38.8190975296027 -1.07702120683888 49 10097 9910.49213289309 13.2808037652791 182.168587995894 0.207439205435006 50 9115 9905.37675107412 13.0450385086054 -785.417047391779 -0.237059055135468 51 10411 9938.6322402809 13.3070737087724 466.930501707991 0.259948829123201 52 9678 9935.923123027 13.0925556965901 -253.626582992084 -0.205530061161791 53 10408 10066.4191878147 14.7240773602836 310.164386097227 1.50389692829314 54 10153 10125.6607407455 15.3600192524281 15.4416286162978 0.569875235783153 55 10368 10166.0024021013 15.7206339303438 195.319140745744 0.319984469395506 56 10581 10157.4915481579 15.3740444908598 429.996697332405 -0.310858783965662 57 10597 10218.6929544714 16.011928202627 366.007259506659 0.589101515682277 58 10680 10303.7745918823 16.9350992352333 357.640070605249 0.889703993818281 59 9738 10351.2567645832 17.3246716653247 -621.495214301556 0.394172004921958 60 9556 10221.0989987519 15.5262153117186 -625.256179984303 -1.90539595655157

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/1bmhq1259939165.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/1bmhq1259939165.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/2l8vb1259939165.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/2l8vb1259939165.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/3hya11259939165.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/3hya11259939165.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/4cc6x1259939165.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/4cc6x1259939165.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/5cbwh1259939165.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259939288pkptiqcnht5im2l/5cbwh1259939165.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')

Copyright

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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