Ad hoc techniek 3

*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 06:44:57 -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/t1259934372kfxla38c20ahi4i.htm/, Retrieved Fri, 04 Dec 2009 14:46:18 +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/t1259934372kfxla38c20ahi4i.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 «

562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 557 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516 528

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 1 562 562 0 0 0 2 561 561.339634174108 -0.68843476512112 -0.339634174107586 -0.102939394850636 3 555 556.30167002153 -3.53750737950236 -1.30167002153033 -0.361798347297018 4 544 546.172760882981 -8.09272615414227 -2.17276088298104 -0.590130913529773 5 537 536.735724180028 -9.01180035987964 0.264275819972285 -0.111732493912854 6 543 539.04938506565 -1.37767196983302 3.9506149343501 0.937184990104925 7 594 580.494308601945 27.5883280943792 13.5056913980552 3.56271197220082 8 611 613.88262978725 31.5182883941516 -2.88262978725027 0.482653410588391 9 613 621.988478073247 15.6535592313344 -8.98847807324663 -1.94848619216758 10 611 616.115159527653 1.06969186910092 -5.11515952765285 -1.79122630472807 11 594 598.374965528423 -11.6711826619275 -4.37496552842256 -1.56482868994634 12 595 591.465311091863 -8.44608365089035 3.53468890813752 0.39610552935425 13 591 589.01389056506 -4.39877114673587 1.9861094349401 0.498878384092907 14 589 587.295628129704 -2.58121187593471 1.70437187029575 0.226855833739574 15 584 582.462954841753 -4.0626675259225 1.53704515824712 -0.180502321925800 16 573 573.14714247557 -7.48180281364099 -0.147142475570026 -0.426441453102353 17 567 568.395244040748 -5.68477039906724 -1.39524404074807 0.221656478094008 18 569 576.303965613224 3.19725889977592 -7.30396561322415 1.08661119861124 19 621 604.109321407278 19.2226737235713 16.8906785927223 1.96869232053014 20 629 626.740343320033 21.4465947089291 2.25965667996701 0.273316763573875 21 628 635.049302764181 12.8657686441724 -7.049302764181 -1.05381569760183 22 612 619.824942476355 -5.4820767200239 -7.82494247635457 -2.25358414995367 23 595 602.87003233706 -12.9721761514677 -7.87003233706008 -0.91996411628555 24 597 593.55878515879 -10.5849499685856 3.4412148412095 0.293329406862227 25 593 589.646999973984 -6.23248273551301 3.35300002601576 0.536273166054448 26 590 585.735052774875 -4.71693547254 4.26494722512517 0.186443412766483 27 580 576.128187072909 -7.88254306910585 3.87181292709132 -0.3876692107905 28 574 571.679609754655 -5.67052766740574 2.32039024534491 0.272859198586681 29 573 576.387572851837 1.05036947512808 -3.38757285183711 0.82879433616291 30 573 588.021480555575 7.8982255336608 -15.0214805555750 0.839675465019677 31 620 604.29655454765 13.3000682681884 15.7034454523500 0.66276192593235 32 626 619.482336143825 14.5163406972291 6.51766385617465 0.149429548313448 33 620 621.40057097307 6.38149809770838 -1.40057097307061 -0.999203236606412 34 588 600.450234103075 -11.2715551472926 -12.4502341030745 -2.16813123617085 35 566 577.750520223269 -18.6492876437219 -11.7505202232692 -0.906194760502808 36 557 556.446677170891 -20.362194918674 0.553322829109256 -0.210538900179225 37 561 551.744964624392 -10.2490923931874 9.25503537560788 1.24420719543982 38 549 542.17575217975 -9.81015129680633 6.8242478202497 0.0539067498620301 39 532 528.98393872936 -11.9838493807184 3.01606127063958 -0.266600580262813 40 526 524.104180887514 -7.4280373692204 1.89581911248584 0.560577218702211 41 511 518.840730796659 -6.03627972179115 -7.84073079665896 0.171377174725085 42 499 517.654312954973 -2.91597887486632 -18.6543129549731 0.383108997287234 43 555 535.269755427318 10.2673767077247 19.7302445726816 1.61746664236007 44 565 553.004620317416 15.0590464716619 11.9953796825837 0.58841122804794 45 542 542.38985254972 -1.42450813442845 -0.389852549719771 -2.02469278590887 46 527 534.957312465606 -5.28304715631302 -7.95731246560575 -0.473936141250455 47 510 523.486083315946 -9.25659062853895 -13.4860833159456 -0.488141262593637 48 514 517.587458824783 -7.1002426387394 -3.58745882478307 0.265035687803791 49 517 508.241128634468 -8.54343223544694 8.75887136553227 -0.177396633467984 50 508 499.142652389282 -8.89984016343441 8.8573476107175 -0.0437556608483276 51 493 490.833980783745 -8.52123700864092 2.16601921625509 0.0464625792082002 52 490 486.328502361258 -5.95267678554692 3.6714976387422 0.315796315503607 53 469 480.072604406743 -6.14691457445949 -11.0726044067432 -0.0238976370997597 54 478 497.702801835814 9.09701864089559 -19.7028018358138 1.87259509707129 55 528 511.038927314717 11.81185210855 16.9610726852829 0.333178849774093 56 534 515.505144116937 7.11189170466540 18.4948558830632 -0.577010952359098 57 518 517.411063808219 3.78091839241226 0.588936191781156 -0.409113871218731 58 506 514.369684157575 -0.585149174345899 -8.36968415757522 -0.536337412367532 59 502 515.800597561215 0.70519518619107 -13.8005975612148 0.158541580600858 60 516 518.231884386885 1.8102892578221 -2.23188438688496 0.135812597659675 61 528 518.868839313513 1.05882769470306 9.1311606864867 -0.0923275176192655

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/1its81259934294.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/1its81259934294.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/2agfo1259934294.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/2agfo1259934294.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/3y5l51259934294.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/3y5l51259934294.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/4kada1259934294.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/4kada1259934294.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/5qkyx1259934294.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259934372kfxla38c20ahi4i/5qkyx1259934294.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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