STSM - bev.aantal

*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: Mon, 20 Dec 2010 13:28:47 +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/20/t1292851709gn343wqtx2ncdvo.htm/, Retrieved Mon, 20 Dec 2010 14:28:35 +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/20/t1292851709gn343wqtx2ncdvo.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 «

16306977 16307888 16307482 16308869 16311019 16312596 16315238 16319511 16327575 16330818 16331930 16334210 16334715 16335459 16334090 16333559 16334600 16336676 16337253 16342333 16348917 16352678 16352972 16357992 16359133 16362938 16365065 16367596 16371278 16374541 16377339 16383275 16393843 16399139 16401009 16405399 16409106 16414307 16418055 16423337 16428686 16434935 16440452 16449092 16464859 16473709 16479291 16485787 16489042 16495231 16501683 16506782 16513615 16520661 16528400 16538542 16554596 16562317 16568499 16574989

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 'Gwilym Jenkins' @ 72.249.127.135 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 16306977 16306977 0 0 0 2 16307888 16307769.6479338 802.429049481105 118.352066160875 0.596812355298189 3 16307482 16307743.9254104 159.003088416110 -261.925410406686 -0.480529304271365 4 16308869 16308689.3026867 793.076169037753 179.697313260461 0.442252697891651 5 16311019 16310832.9242033 1862.70797688004 186.075796733849 0.742740018322194 6 16312596 16312684.0558317 1853.52272502671 -88.0558316668831 -0.00639744523962094 7 16315238 16315142.9043079 2334.35981980677 95.0956920658428 0.334609318661443 8 16319511 16319237.7020088 3732.75073843248 273.297991176963 0.973170392718777 9 16327575 16326957.1334659 6899.09117146745 617.866534127253 2.20350686356295 10 16330818 16331475.1574874 5008.07321314193 -657.157487428788 -1.31598636352216 11 16331930 16332538.1536815 1874.89231978793 -608.153681536321 -2.18042618470508 12 16334210 16334079.2469868 1609.78577870023 130.753013182522 -0.184491476964418 13 16334715 16334826.7444229 926.091133625024 -111.744422934432 -0.476802917964902 14 16335459 16335151.4000672 447.847366270083 307.59993282131 -0.33749539563946 15 16334090 16334618.117871 -298.049741571975 -528.117871009226 -0.520077635925116 16 16333559 16333754.7003244 -731.900000761233 -195.700324355116 -0.305053408189535 17 16334600 16334072.7837556 71.2442703724557 527.216244442828 0.557250449839938 18 16336676 16336231.4863797 1662.18099228068 444.51362028547 1.10725994173139 19 16337253 16337524.1166632 1380.12465440747 -271.116663239638 -0.196343358778851 20 16342333 16342435.6136316 4076.61774239966 -102.613631619211 1.87645403719288 21 16348917 16347890.6488007 5129.13450623755 1026.35119932635 0.732463197758377 22 16352678 16352698.5968288 4883.8971386203 -20.5968287699800 -0.170667100787337 23 16352972 16354257.2719908 2345.22375635811 -1285.27199079785 -1.76670740081873 24 16357992 16357468.0620039 3005.63222097429 523.937996111849 0.459649119766005 25 16359133 16359405.8328430 2191.04632983813 -272.832843039710 -0.56827557652956 26 16362938 16362200.8702167 2652.35595496233 737.129783275367 0.321476483744732 27 16365065 16365293.3243038 2984.19505624561 -228.324303798122 0.230791017358861 28 16367596 16368017.7250692 2787.99214238032 -421.725069207335 -0.137297869625761 29 16371278 16371018.2731215 2948.79360768452 259.726878492811 0.111818714740832 30 16374541 16373812.8445784 2832.51974293858 728.155421570669 -0.080850396004529 31 16377339 16378127.7928633 3950.47136757629 -788.792863303477 0.778252166564338 32 16383275 16383598.1758963 5097.55420346252 -323.175896299154 0.798293587672257 33 16393843 16392197.4303536 7740.67529984905 1645.56964645016 1.83935192007960 34 16399139 16398728.6118048 6827.78027766495 410.388195184257 -0.635329030874804 35 16401009 16403003.486197 4901.53774300114 -1994.48619698999 -1.3404772077725 36 16405399 16405095.4540239 2782.98676016899 303.545976141113 -1.47494285795660 37 16409106 16409192.3747816 3774.29149833876 -86.3747816425482 0.691067023130556 38 16414307 16413596.7763131 4249.49417686857 710.223686855878 0.330632798218718 39 16418055 16418160.5430980 4485.10969395089 -105.543098029488 0.163895632310000 40 16423337 16423548.7354262 5162.42715779133 -211.735426237306 0.472759137459043 41 16428686 16428291.9387746 4847.38081791848 394.061225427853 -0.219284536099624 42 16434935 16434135.7410467 5594.66001902326 799.258953275607 0.519578141479515 43 16440452 16441304.0404970 6774.24722315774 -852.040497029385 0.820976447031814 44 16449092 16450121.2722794 8306.68993293857 -1029.27227938766 1.06654219208397 45 16464859 16462393.9699166 11282.4038547928 2465.03008344967 2.07080225025958 46 16473709 16472938.9264246 10729.1228671495 770.073575354833 -0.385049269862007 47 16479291 16481031.4089633 8751.70695851332 -1740.40896331086 -1.37612014232664 48 16485787 16486410.7276573 6223.40967259856 -623.727657251446 -1.76040189691263 49 16489042 16489783.6976704 4085.16478635051 -741.697670374698 -1.48962248093219 50 16495231 16494443.1340520 4515.60734023491 787.865948037781 0.299424906629549 51 16501683 16501480.8014666 6399.5827438526 202.1985333551 1.31072720351576 52 16506782 16506931.2948615 5690.51396384101 -149.294861518056 -0.494327611006217 53 16513615 16513076.1797275 6030.51567022144 538.82027247273 0.236716011241474 54 16520661 16519847.5436199 6584.28848106541 813.456380054838 0.385112131890457 55 16528400 16529189.1650437 8643.8766878351 -789.16504367954 1.43315819182033 56 16538542 16540342.1744051 10518.8945209348 -1800.17440510935 1.30495496219462 57 16554596 16552054.3315249 11410.8848158281 2541.66847509516 0.62074453128931 58 16562317 16561519.7747520 9956.67739629438 797.225247964324 -1.01201261439228 59 16568499 16569739.0854073 8658.4253068564 -1240.08540732774 -0.90352086081914 60 16574989 16575388.4899152 6410.18136671235 -399.489915176402 -1.56536530441666

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/1za1m1292851723.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/1za1m1292851723.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/2ak071292851723.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/2ak071292851723.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/3kbia1292851723.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/3kbia1292851723.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/4kbia1292851723.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/4kbia1292851723.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/5kbia1292851723.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851709gn343wqtx2ncdvo/5kbia1292851723.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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