Indicator van het consumentenvertrouwen

*Unverified author*

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

Title produced by software: Exponential Smoothing

Date of computation: Mon, 31 May 2010 13:30:53 +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/May/31/t127531292384vs8nsemsvusdk.htm/, Retrieved Mon, 31 May 2010 15:35:23 +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/May/31/t127531292384vs8nsemsvusdk.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 «

-15 -15 -10 -12 -11 -11 -17 -18 -19 -22 -24 -24 -20 -25 -22 -17 -9 -11 -13 -11 -9 -7 -3 -3 -6 -4 -8 -1 -2 -2 -1 1 2 2 -1 1 -1 -8 1 2 -2 -2 -2 -2 -6 -4 -5 -2 -1 -5 -9 -8 -14 -10 -11 -11 -11 -5 -2 -3 -6 -6 -7 -6 -2 -2 -4 0 -6 -4 -3 -1 -3

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Estimated Parameters of Exponential Smoothing Parameter Value alpha 0.793304674764876 beta FALSE gamma FALSE Interpolation Forecasts of Exponential Smoothing t Observed Fitted Residuals 2 -15 -15 0 3 -10 -15 5 4 -12 -11.0334766261756 -0.966523373824378 5 -11 -11.8002241369000 0.80022413690002 6 -11 -11.1654025882375 0.165402588237546 7 -17 -11.0341879417705 -5.96581205822951 8 -18 -15.7668945363326 -2.23310546366737 9 -19 -17.5384275399029 -1.46157246009706 10 -22 -18.6978998050055 -3.30210019499446 11 -24 -21.3174713262367 -2.68252867376335 12 -24 -23.4455338633239 -0.554466136676062 13 -20 -23.8853944415479 3.88539444154788 14 -25 -20.8030928677625 -4.19690713223752 15 -22 -24.1325189153206 2.13251891532055 16 -17 -22.4407816907722 5.44078169077224 17 -9 -18.1245841411075 9.12458414110748 18 -11 -10.8860088866815 -0.113991113318532 19 -13 -10.9764385697587 -2.02356143024129 20 -11 -12.5817393120430 1.58173931204302 21 -9 -11.3269381215399 2.32693812153991 22 -7 -9.4809672318337 2.4809672318337 23 -3 -7.51280432888155 4.51280432888155 24 -3 -3.93277555848065 0.93277555848065 25 -6 -3.19280034743153 -2.80719965256847 26 -4 -5.41976495481243 1.41976495481243 27 -8 -4.29345877909239 -3.70654122090761 28 -1 -7.2338752568471 6.23387525684711 29 -2 -2.28851287368921 0.288512873689207 30 -2 -2.05963426226171 0.059634262261711 31 -1 -2.01232612323334 1.01232612323334 32 1 -1.20924307728573 2.20924307728573 33 2 0.543359783616979 1.45664021638302 34 2 1.69891927672415 0.301080723275850 35 -1 1.93776802198047 -2.93776802198047 36 1 -0.392777083231398 1.39277708323140 37 -1 0.712119487801458 -1.71211948780146 38 -8 -0.646112905627483 -7.35388709437252 39 1 -6.47998591528629 7.47998591528629 40 2 -0.546078121514249 2.54607812151425 41 -2 1.47373755459958 -3.47373755459958 42 -2 -1.28199468637057 -0.718005313629425 43 -2 -1.85159165817882 -0.148408341821181 44 -2 -1.96932468951967 -0.0306753104803346 45 -6 -1.99365955672358 -4.00634044327642 46 -4 -5.17190815907435 1.17190815907435 47 -5 -4.24222793808557 -0.757772061914432 48 -2 -4.84337205720851 2.84337205720851 49 -1 -2.58771171212918 1.58771171212918 50 -5 -1.32817258871816 -3.67182741128184 51 -9 -4.24105043901785 -4.75894956098215 52 -8 -8.01634737271524 0.0163473727152432 53 -14 -8.00337892552012 -5.99662107447988 54 -10 -12.7605264566986 2.76052645669858 55 -11 -10.5705879137875 -0.429412086212521 56 -11 -10.9112425291804 -0.0887574708195906 57 -11 -10.9816542457019 -0.0183457542981031 58 -5 -10.9962080183487 5.99620801834867 59 -2 -6.23938816653004 4.23938816653004 60 -3 -2.87626171587886 -0.123738284121136 61 -6 -2.97442387511955 -3.02557612488045 62 -6 -5.37462755884421 -0.625372441155792 63 -7 -5.87073843988222 -1.12926156011778 64 -6 -6.76658691455593 0.766586914555932 65 -2 -6.15844993162513 4.15844993162513 66 -2 -2.85953216109124 0.859532161091237 67 -4 -2.17766127958680 -1.82233872041320 68 0 -3.62333110549563 3.62333110549563 69 -6 -0.748925601284963 -5.25107439871504 70 -4 -4.91462746932376 0.91462746932376 71 -3 -4.18904922224085 1.18904922224085 72 -1 -3.24577091571164 2.24577091571164 73 -3 -1.46419034982660 -1.53580965017340 Extrapolation Forecasts of Exponential Smoothing t Forecast 95% Lower Bound 95% Upper Bound 74 -2.68255532485817 -8.9792015164491 3.61409086673277 75 -2.68255532485817 -10.7199283590041 5.35481770928781 76 -2.68255532485817 -12.1456931405067 6.78058249079036 77 -2.68255532485817 -13.3831435958785 8.01803294616215 78 -2.68255532485817 -14.4916281662728 9.12651751655651 79 -2.68255532485817 -15.5046383616263 10.13952771191 80 -2.68255532485817 -16.4432757067902 11.0781650570738 81 -2.68255532485817 -17.3218530353926 11.9567423856763 82 -2.68255532485817 -18.1506078682651 12.7854972185488 83 -2.68255532485817 -18.9371627182571 13.5720520685408 84 -2.68255532485817 -19.6873744518433 14.3222638021270 85 -2.68255532485817 -20.4058587858222 15.0407481361059

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/31/t127531292384vs8nsemsvusdk/15tuc1275312648.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/31/t127531292384vs8nsemsvusdk/15tuc1275312648.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/31/t127531292384vs8nsemsvusdk/2gltx1275312648.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/31/t127531292384vs8nsemsvusdk/2gltx1275312648.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/31/t127531292384vs8nsemsvusdk/3gltx1275312648.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/31/t127531292384vs8nsemsvusdk/3gltx1275312648.ps (open in new window)

Parameters (Session):

par1 = 12 ; par2 = Single ; par3 = multiplicative ;

Parameters (R input):

par1 = 12 ; par2 = Single ; 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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