Maandelijkse cijfers werkloosheid 2004-2010

*Unverified author*

R Software Module: /rwasp_exponentialsmoothing.wasp (opens new window with default values)

Title produced by software: Exponential Smoothing

Date of computation: Wed, 02 Jun 2010 08:51:22 +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/Jun/02/t1275468764urz354lhuhh7pgr.htm/, Retrieved Wed, 02 Jun 2010 10:52:45 +0200

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/Jun/02/t1275468764urz354lhuhh7pgr.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:

KDGP2W62

Dataseries X:

» Textbox « » Textfile « » CSV «

580 575 558 564 581 597 587 536 524 537 536 533 528 516 502 506 518 534 528 478 469 490 493 508 517 514 510 527 542 565 555 499 511 526 532 549 561 557 566 588 620 626 620 573 573 574 580 590 593 597 595 612 628 629 621 569 567 573 584 589 591 595 594 611 613 611 594 543 537 544 555 561 562

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Estimated Parameters of Exponential Smoothing Parameter Value alpha 0.811699206863691 beta 0.698542100789111 gamma 1 Interpolation Forecasts of Exponential Smoothing t Observed Fitted Residuals 13 528 557.922684722142 -29.9226847221424 14 516 504.985239426392 11.0147605736081 15 502 489.663927930474 12.3360720695259 16 506 499.828350664313 6.17164933568688 17 518 515.972187977801 2.02781202219933 18 534 532.970597817396 1.02940218260392 19 528 531.104441925337 -3.10444192533748 20 478 482.285441358656 -4.28544135865587 21 469 465.432594594073 3.56740540592727 22 490 479.259005228635 10.7409947713649 23 493 492.846442883026 0.153557116974355 24 508 496.348780554203 11.6512194457973 25 517 508.376869735463 8.62313026453728 26 514 528.589728203554 -14.5897282035536 27 510 511.985660040853 -1.98566004085342 28 527 520.783392951383 6.21660704861677 29 542 548.437020320311 -6.43702032031149 30 565 566.40612780695 -1.40612780695005 31 555 567.485189897755 -12.4851898977553 32 499 508.858460230444 -9.85846023044382 33 511 485.952947615765 25.0470523842353 34 526 529.655536278595 -3.65553627859458 35 532 531.268330064569 0.731669935431455 36 549 539.618453729242 9.38154627075812 37 561 549.35980820104 11.6401917989602 38 557 569.553232218153 -12.5532322181531 39 566 559.72301368191 6.27698631809051 40 588 585.8550792479 2.14492075210023 41 620 615.32355318812 4.67644681188051 42 626 658.955127329477 -32.9551273294775 43 620 626.880318524231 -6.88031852423103 44 573 566.206458202869 6.79354179713096 45 573 570.992389696145 2.0076103038549 46 574 586.461483491403 -12.4614834914028 47 580 571.248324422297 8.7516755777026 48 590 581.966968799496 8.0330312005043 49 593 583.588958021232 9.41104197876837 50 597 588.759268924386 8.24073107561446 51 595 602.668128288203 -7.66812828820298 52 612 612.783174609366 -0.783174609365915 53 628 634.76138608244 -6.76138608243957 54 629 648.972535709871 -19.9725357098707 55 621 626.481679579038 -5.48167957903843 56 569 564.646871190517 4.35312880948345 57 567 560.445069744188 6.55493025581222 58 573 573.091463343326 -0.0914633433263816 59 584 575.309684723872 8.69031527612822 60 589 589.270115136402 -0.270115136401614 61 591 583.110089541434 7.88991045856551 62 595 584.730691311106 10.2693086888941 63 594 596.339202920928 -2.33920292092773 64 611 614.130133911347 -3.13013391134746 65 613 633.807436630685 -20.8074366306846 66 611 626.402002233322 -15.402002233322 67 594 605.333710089779 -11.3337100897794 68 543 534.773495842194 8.22650415780572 69 537 528.643846670708 8.3561533292924 70 544 536.407767125581 7.59223287441876 71 555 545.893027476715 9.10697252328453 72 561 558.320150856424 2.67984914357612 73 562 558.029040514368 3.97095948563231 Extrapolation Forecasts of Exponential Smoothing t Forecast 95% Lower Bound 95% Upper Bound 74 556.846094315295 535.968093672714 577.724094957877 75 552.109219829979 516.917706840608 587.300732819349 76 565.915888503798 511.615199170959 620.216577836638 77 580.581005338465 503.573374408028 657.588636268902 78 598.884428951282 495.397014171471 702.371843731094 79 608.429558402593 477.065378531278 739.793738273908 80 572.074063850002 422.261660783816 721.886466916188 81 576.959654924434 397.978196574608 755.94111327426 82 591.640772587362 378.176151978137 805.105393196587 83 604.903714443352 354.81661333167 854.990815555034 84 612.822622438737 326.074549841523 899.57069503595 85 612.463691973161 292.119083229454 932.808300716867

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jun/02/t1275468764urz354lhuhh7pgr/1m4ul1275468678.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275468764urz354lhuhh7pgr/1m4ul1275468678.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275468764urz354lhuhh7pgr/2m4ul1275468678.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275468764urz354lhuhh7pgr/2m4ul1275468678.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275468764urz354lhuhh7pgr/3m4ul1275468678.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275468764urz354lhuhh7pgr/3m4ul1275468678.ps (open in new window)

Parameters (Session):

par1 = 12 ; par2 = Triple ; par3 = multiplicative ;

Parameters (R input):

par1 = 12 ; par2 = Triple ; par3 = multiplicative ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) if (par2 == 'Single') K <- 1 if (par2 == 'Double') K <- 2 if (par2 == 'Triple') K <- par1 nx <- length(x) nxmK <- nx - K x <- ts(x, frequency = par1) if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F) if (par2 == 'Double') fit <- HoltWinters(x, gamma=F) if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3) fit myresid <- x - fit$fitted[,'xhat'] bitmap(file='test1.png') op <- par(mfrow=c(2,1)) plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing') plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors') par(op) dev.off() bitmap(file='test2.png') p <- predict(fit, par1, prediction.interval=TRUE) np <- length(p[,1]) plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing') dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF') spectrum(myresid,main='Residals Periodogram') cpgram(myresid,main='Residal Cumulative Periodogram') qqnorm(myresid,main='Residual Normal QQ Plot') qqline(myresid) par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,fit$alpha) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,fit$beta) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'gamma',header=TRUE) a<-table.element(a,fit$gamma) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,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,'Fitted',header=TRUE) a<-table.element(a,'Residuals',header=TRUE) a<-table.row.end(a) for (i in 1:nxmK) { a<-table.row.start(a) a<-table.element(a,i+K,header=TRUE) a<-table.element(a,x[i+K]) a<-table.element(a,fit$fitted[i,'xhat']) a<-table.element(a,myresid[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Extrapolation Forecasts of Exponential Smoothing',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Forecast',header=TRUE) a<-table.element(a,'95% Lower Bound',header=TRUE) a<-table.element(a,'95% Upper Bound',header=TRUE) a<-table.row.end(a) for (i in 1:np) { a<-table.row.start(a) a<-table.element(a,nx+i,header=TRUE) a<-table.element(a,p[i,'fit']) a<-table.element(a,p[i,'lwr']) a<-table.element(a,p[i,'upr']) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.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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