STSM - werkloosheid

*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 13:31:59 +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/t1292851800p8bc7ytq7g2orr2.htm/, Retrieved Mon, 20 Dec 2010 14:30:06 +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/t1292851800p8bc7ytq7g2orr2.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 «

493 514 522 490 484 506 501 462 465 454 464 427 460 473 465 422 415 413 420 363 376 380 384 346 389 407 393 346 348 353 364 305 307 312 312 286 324 336 327 302 299 311 315 264 278 278 287 279 324 354 354 360 363 385 412 370 389 395 417 404

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 6 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 493 493 0 0 0 2 514 504.571033348849 3.14242806259559 9.42896665115085 1.76691629309249 3 522 520.007446945454 7.4837907567722 1.99255305454630 1.23183215236965 4 490 506.574978572565 -1.37237606501525 -16.5749785725646 -2.12227545364971 5 484 488.710568130579 -8.639501661703 -4.71056813057891 -1.59055060027424 6 506 493.561262728594 -2.76880717502389 12.4387372714058 1.28279545481015 7 501 498.773900112680 0.689303630683884 2.22609988731953 0.768261258051414 8 462 477.46497312555 -8.87297564973663 -15.4649731255497 -2.13631655926010 9 465 463.087216928793 -11.2726669164339 1.91278307120683 -0.536233728014627 10 454 452.173628671692 -11.1159804348238 1.82637132830787 0.0350066531413511 11 464 454.930611568434 -5.06227414424436 9.06938843156578 1.35251809408963 12 427 437.668444233094 -10.3847382757294 -10.6684442330937 -1.18915900585750 13 460 448.793092570577 -1.18661461560132 11.2069074294229 2.15392038600191 14 473 461.817642396312 4.95437066428956 11.1823576036883 1.37767126090792 15 465 459.518769099383 1.94216779933184 5.48123090061652 -0.656853657086611 16 422 444.329408514776 -5.13641618829899 -22.3294085147756 -1.60475087331948 17 415 431.084306116483 -8.55739224066271 -16.0843061164830 -0.774225276626705 18 413 409.973112057597 -13.8799150438736 3.02688794240324 -1.18307750176295 19 420 401.826319177325 -11.461016113609 18.1736808226748 0.536540822031456 20 363 382.296320682616 -14.8598651647699 -19.2963206826162 -0.757455201188811 21 376 371.011564421791 -13.3514902747804 4.98843557820949 0.336916973855627 22 380 372.938482022992 -6.89782280644421 7.06151797700794 1.44206767783673 23 384 371.408407265191 -4.6323229176987 12.5915927348095 0.506534429325817 24 346 368.550652855417 -3.88437736920351 -22.5506528554166 0.16780449449934 25 389 376.525720101599 1.12418941932652 12.4742798984014 1.12969771546276 26 407 387.102998592958 5.1150566321202 19.8970014070423 0.891201994671527 27 393 385.218524927309 2.19508898861061 7.78147507269059 -0.647287238808744 28 346 372.065083949765 -4.16863561400948 -26.0650839497649 -1.42613513215525 29 348 360.851992985825 -7.10806307933134 -12.8519929858245 -0.662430282001851 30 353 351.343652640777 -8.11509328915523 1.65634735922331 -0.225423644293794 31 364 342.070796780096 -8.6002651201675 21.9292032199044 -0.108003468651413 32 305 329.320108629591 -10.3347944485435 -24.3201086295909 -0.386215234726404 33 307 312.262069318856 -13.1417350570144 -5.26206931885617 -0.626331221209646 34 312 303.310588476613 -11.3923424763325 8.68941152338655 0.391010452837393 35 312 298.641333580546 -8.5851984461404 13.358666419454 0.628496124810071 36 286 306.485381197079 -1.71850775064605 -20.4853811970791 1.540178885019 37 324 313.018212411979 1.73605379623659 10.9817875880213 0.774202772509078 38 336 313.435138455715 1.18455003251128 22.5648615442849 -0.12298495952208 39 327 312.65755371924 0.368841704111837 14.3424462807603 -0.181531695080490 40 302 320.232748430545 3.35428699579593 -18.2327484305448 0.66770852676506 41 299 316.67239551931 0.482764751821045 -17.6723955193100 -0.64492546775473 42 311 310.691349745327 -2.21139797913897 0.308650254673188 -0.603795074957681 43 315 296.117659991278 -7.3655353187369 18.8823400087221 -1.15011773889491 44 264 284.870189599966 -8.98034151744165 -20.8701895999657 -0.359736754979694 45 278 281.277263731508 -6.74398809596575 -3.27726373150823 0.498782918050458 46 278 274.92418785064 -6.58183781716956 3.07581214936003 0.0362453251890144 47 287 276.740988406644 -3.09585557811918 10.2590115933563 0.780775914220422 48 279 292.470348322266 4.73039338193652 -13.4703483222662 1.75396508851009 49 324 308.635196829046 9.48938047789489 15.3648031709538 1.06457432972693 50 354 327.90365786262 13.5537917240268 26.0963421373798 0.906359214920433 51 354 343.360562171018 14.3420325061335 10.6394378289824 0.175663553763780 52 360 368.099389787243 18.6390606994307 -8.09938978724268 0.960553163847438 53 363 381.158503053108 16.3300326177234 -18.1585030531083 -0.517671939646797 54 385 384.798878262741 11.0659837578906 0.201121737258704 -1.17936373343546 55 412 391.411194084666 9.21733318770302 20.5888059153339 -0.412931112201856 56 370 394.881345970172 6.83571197043593 -24.8813459701715 -0.530939027598221 57 389 395.32728359129 4.19347876811356 -6.32728359128969 -0.589340664512528 58 395 397.533888222596 3.37267569384741 -2.53388822259636 -0.183456442636117 59 417 410.266516996304 7.24203331567254 6.73348300369594 0.866445181414434 60 404 422.481743874837 9.30109927695227 -18.4817438748371 0.461154741842772

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/1e9ug1292851913.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/1e9ug1292851913.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/2e9ug1292851913.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/2e9ug1292851913.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/37ib11292851913.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/37ib11292851913.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/47ib11292851913.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/47ib11292851913.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/5hsb41292851913.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/20/t1292851800p8bc7ytq7g2orr2/5hsb41292851913.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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