STSM Werkloosheid België 2000 - 2010

*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, 27 Dec 2010 21:04:16 +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/27/t1293483786b31wr7peuzlv0iw.htm/, Retrieved Mon, 27 Dec 2010 22:03:06 +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/27/t1293483786b31wr7peuzlv0iw.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:

Data Paper Statistiek

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

464 460 467 460 448 443 436 431 484 510 513 503 471 471 476 475 470 461 455 456 517 525 523 519 509 512 519 517 510 509 501 507 569 580 578 565 547 555 562 561 555 544 537 543 594 611 613 611 594 595 591 589 584 573 567 569 621 629 628 612 595 597 593 590 580 574 573 573 620 626 620 588 566 557 561 549 532 526 511 499 555 565 542 527 510 514 517 508 493 490 469 478 528 534 518 506 502 516 528 533 536 537 524 536 587 597 581 564 558 575 580 575 563 552 537 545 601 604 586 564 549

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 464 464 0 0 0 2 460 460.872492770137 -2.89547459139159 -0.872492770137255 -0.437932871790245 3 467 464.534010172414 1.66348640315731 2.46598982758586 0.615780667897815 4 460 461.68774765858 -1.62908509915099 -1.68774765858020 -0.427947674290657 5 448 450.088267307691 -8.77442843993639 -2.08826730769144 -0.909693445081838 6 443 441.925343116354 -8.33706936402289 1.07465688364624 0.0561662564630144 7 436 435.436724138177 -7.01129814034415 0.563275861823064 0.170125037983934 8 431 430.480636362847 -5.53666977674634 0.519363637152588 0.189170319451585 9 484 471.703173065543 28.007339812674 12.2968269344575 4.30339277564414 10 510 510.708519696514 35.8957696234027 -0.708519696513995 1.01200030845752 11 513 520.600127030981 17.2446651071005 -7.6001270309806 -2.3927324689141 12 503 508.516603552013 -3.79106131615576 -5.51660355201253 -2.69865487675498 13 471 476.955816234104 -23.6100401341582 -5.9558162341044 -2.57725720878067 14 471 468.574757930799 -12.8111586014859 2.42524206920097 1.39288443075299 15 476 470.369565626795 -2.80071813408438 5.63043437320517 1.28469357873321 16 475 473.49172728349 1.29398589587938 1.50827271650973 0.531794163557651 17 470 472.486398899084 -0.300047791541838 -2.48639889908361 -0.203882936100846 18 461 460.276644533241 -8.50552496646556 0.723355466759105 -1.05074932943788 19 455 451.504181733445 -8.68960678903854 3.49581826655529 -0.0236297959493695 20 456 463.012983517492 5.25919541927106 -7.01298351749206 1.78959414917582 21 517 502.016714254175 28.5685810069758 14.9832857458246 2.99021699833202 22 525 524.701499010176 24.5046574221663 0.29850098982403 -0.521391511920852 23 523 528.333520876983 10.0964013485292 -5.33352087698307 -1.84842075377375 24 519 519.840949627513 -2.71864902685499 -0.840949627513182 -1.64575978008237 25 509 517.73675148373 -2.29467521402451 -8.73675148372991 0.0546375838952372 26 512 514.824267782549 -2.72001839899528 -2.82426778254896 -0.0545297429713751 27 519 515.249903836116 -0.579430341831003 3.75009616388409 0.274414713557978 28 517 514.634088660447 -0.604234923553658 2.36591133955312 -0.00320066640428567 29 510 508.232503067488 -4.57314717576175 1.76749693251153 -0.509255256277633 30 509 505.035966606301 -3.63381599131519 3.96403339369906 0.120258415067751 31 501 503.177114186951 -2.42386161564514 -2.17711418695127 0.155220815350135 32 507 520.374795708636 10.9687285515189 -13.3747957086362 1.71847366571448 33 569 549.58446892411 23.4266267215222 19.4155310758902 1.59816642606443 34 580 574.254220882156 24.2755173318819 5.74577911784408 0.108906741015679 35 578 582.340073100867 13.2287383420504 -4.34007310086673 -1.41733633240608 36 565 571.938643506312 -2.88616961764111 -6.9386435063124 -2.06999186436671 37 547 558.093691666969 -10.3670701403794 -11.0936916669689 -0.961637941388303 38 555 556.559279037694 -4.34959108040741 -1.55927903769359 0.771212589373182 39 562 557.1554401038 -0.9992127287295 4.84455989620052 0.429606186050208 40 561 555.978192899712 -1.11988511959036 5.02180710028839 -0.0155283843019614 41 555 552.22108286149 -2.91284824030054 2.77891713851007 -0.230222160945093 42 544 541.176329963348 -8.43431173092106 2.82367003665162 -0.707371001497586 43 537 542.42627656832 -1.86763503505914 -5.4262765683195 0.842033576111527 44 543 559.01818927713 10.6571149330045 -16.0181892771299 1.6069655604421 45 594 575.750806465718 14.7820273942630 18.2491935342818 0.529188180035347 46 611 598.737205529999 20.3518503113943 12.2627944700010 0.714553918245582 47 613 611.942306653027 15.5026395108704 1.05769334697272 -0.622255653944599 48 611 617.022281606431 8.4306270380436 -6.02228160643142 -0.908207095891904 49 594 611.645089643879 -0.943975771545664 -17.6450896438786 -1.20374580176994 50 595 600.829579681121 -7.63495681938113 -5.82957968112068 -0.857654462791544 51 591 587.414745750952 -11.5397692980889 3.58525424904767 -0.500792090815439 52 589 580.456403893974 -8.44387208707841 8.54359610602583 0.397897529985553 53 584 576.149652939137 -5.64234888469052 7.85034706086335 0.359741723277606 54 573 571.914070307972 -4.69007525673535 1.08592969202786 0.122070388582348 55 567 575.461676723053 0.879754214437346 -8.46167672305341 0.71411295160094 56 569 585.455236740751 7.04241106297723 -16.4552367407509 0.790564126220589 57 621 603.714875290632 14.6308968180314 17.2851247093681 0.973554355619095 58 629 616.669247047648 13.4967200102927 12.3307529523525 -0.145511996603899 59 628 625.716299421715 10.4871919194064 2.28370057828451 -0.386221866887624 60 612 618.765868194923 -1.30959143843142 -6.76586819492296 -1.51457532558114 61 595 610.64992690359 -5.91554618035924 -15.6499269035903 -0.591113507981865 62 597 601.551192239516 -8.06672537159297 -4.55119223951633 -0.275781651761463 63 593 590.940843477381 -9.78206120999331 2.05915652261906 -0.220015702906292 64 590 581.479995825549 -9.56541593365662 8.52000417445081 0.027827141558759 65 580 571.568166134162 -9.7994076334266 8.43183386583773 -0.0300440779980222 66 574 571.955286669993 -2.91843837402978 2.04471333000656 0.882396406653817 67 573 581.578300721041 5.54561390325894 -8.57830072104121 1.08521040793279 68 573 592.661965072958 9.28215093953225 -19.6619650729582 0.479274286089763 69 620 603.206817242927 10.1342793227535 16.7931827570731 0.109322827164236 70 626 613.05239238666 9.93943573641825 12.9476076133400 -0.0250000634811991 71 620 614.951857699467 4.51325543863037 5.04814230053254 -0.696395792846227 72 588 598.373247866715 -9.72624926917967 -10.3732478667150 -1.82781535662797 73 566 581.781584535404 -14.3616456426709 -15.7815845354038 -0.594729720188353 74 557 561.790582980598 -18.1581838973138 -4.79058298059765 -0.486772819718756 75 561 554.762801491793 -10.6627074118748 6.23719850820688 0.96146032673989 76 549 540.61796726573 -13.0078773771216 8.3820327342698 -0.301126611933101 77 532 526.20343017357 -13.9563087140215 5.79656982643006 -0.121764744092675 78 526 524.416348167366 -5.74957568310293 1.58365183263392 1.05265048824499 79 511 521.485094848084 -3.85027057989199 -10.4850948480845 0.243535427952933 80 499 519.686061113771 -2.46855325276647 -20.6860611137709 0.177214938389221 81 555 534.895184022704 9.43911159543427 20.1048159772958 1.52766667527508 82 565 549.414230653588 12.8612874982456 15.5857693464122 0.439126584505279 83 542 537.215288960119 -4.02399940400554 4.78471103988059 -2.16711763700907 84 527 533.71414653142 -3.67158597954126 -6.71414653142028 0.0452299888775267 85 510 525.766297575577 -6.55374828136452 -15.7662975755769 -0.369733101340550 86 514 521.314797922948 -5.13821453477928 -7.3147979229479 0.181507543356025 87 517 510.440442301881 -8.99637103780048 6.55955769811927 -0.494912773312322 88 508 499.008050715408 -10.6349774879903 8.99194928459157 -0.210360455133235 89 493 489.782561484323 -9.68604000342349 3.21743851567673 0.121819365386316 90 490 486.716331278565 -5.22804010532139 3.2836687214354 0.571890039511757 91 469 480.997538120651 -5.55834842414912 -11.9975381206509 -0.042356486505193 92 478 499.15036279227 10.3919450967165 -21.1503627922698 2.04565431111206 93 528 510.284871091188 10.8913809122429 17.7151289088125 0.0640732300381689 94 534 512.83735989979 5.28216759087847 21.1626401002101 -0.719799275261387 95 518 514.250227903731 2.67871508165316 3.74977209626936 -0.334139737656964 96 506 512.926116019943 -0.0154598685750427 -6.92611601994354 -0.345745614193001 97 502 517.29541746451 2.93544878511336 -15.2954174645099 0.378522908274332 98 516 521.173019425913 3.56897909905578 -5.17301942591312 0.081239702319651 99 528 520.993948873366 1.05084492758457 7.00605112663387 -0.323026516109515 100 533 523.197735045716 1.82550429924956 9.80226495428398 0.0994365237780385 101 536 531.912786702685 6.4579124067586 4.0872132973147 0.594641092312073 102 537 535.038210344802 4.21655393111134 1.96178965519809 -0.287552698734617 103 524 542.857827982115 6.63882554154019 -18.8578279821153 0.310635770803925 104 536 556.076653519053 11.0598310116575 -20.0766535190526 0.566993203461195 105 587 567.012517673596 10.9765610377891 19.9874823264035 -0.0106826914600242 106 597 575.102959501497 9.03771344239461 21.8970404985035 -0.248808416582174 107 581 577.681158037392 4.69683904634009 3.31884196260819 -0.557127536576021 108 564 574.360995735981 -0.69234686158514 -10.3609957359809 -0.691552085235307 109 558 573.253973568206 -0.971055962304933 -15.2539735682064 -0.0357495384284554 110 575 577.422130371953 2.48051460287308 -2.4221303719528 0.442627136021326 111 580 574.854912909622 -0.907248253279519 5.14508709037761 -0.434589381591217 112 575 568.147273497916 -4.80040646808459 6.85272650208423 -0.499689452778211 113 563 558.604399692955 -7.98543154912492 4.39560030704525 -0.408822994417209 114 552 551.123130970042 -7.64673959350342 0.876869029957608 0.0434539859838452 115 537 555.31754813776 0.305137789840939 -18.3175481377603 1.01981410865332 116 545 563.864734425462 5.83678990236037 -18.8647344254624 0.709433420998137 117 601 578.32732811217 11.6241793191984 22.6726718878306 0.742456890940871 118 604 582.219334075511 6.43584504317891 21.7806659244891 -0.665814771336709 119 586 581.614822752245 1.71000104319427 4.38517724775509 -0.60652931166299 120 564 576.45248512869 -2.90439233751419 -12.4524851286904 -0.592101856076172 121 549 567.712618180742 -6.82188812838377 -18.7126181807424 -0.502481685409719

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/1fl671293483851.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/1fl671293483851.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/2qc5t1293483851.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/2qc5t1293483851.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/31mmv1293483851.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/31mmv1293483851.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/41mmv1293483851.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/41mmv1293483851.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/51mmv1293483851.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/27/t1293483786b31wr7peuzlv0iw/51mmv1293483851.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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