exponential smoothing niet werkende werkzoekende Sebastiaan Vandesompele

*Unverified author*

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

Title produced by software: Exponential Smoothing

Date of computation: Fri, 20 May 2011 07:31:36 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb.htm/, Retrieved Fri, 20 May 2011 09:30:08 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W102

Dataseries X:

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89507 87562 85209 82360 79054 79069 107551 115759 115585 110260 103444 102303 101397 97994 94044 91159 87239 89235 118647 125620 125154 117529 109459 108483 107137 104699 100804 96066 91971 93228 120144 127233 127166 118194 109940 106683 102834 99882 96666 92540 88744 89321 115870 122401 122030 113802 105791 103076 98658 96945 92497 90687 88796 90015 113228 118711 117460 106556 97347 92657 93118 89037 83570 81693 75956 73993 97088 102394 96549 89727 82336 82653 82303 79596 74472 73562 66618 69029 89899 93774 90305 83799 80320 82497

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 'George Udny Yule' @ 216.218.223.82 Estimated Parameters of Exponential Smoothing Parameter Value alpha 1 beta 0.092298193665188 gamma 0.433108278636975 Interpolation Forecasts of Exponential Smoothing t Observed Fitted Residuals 13 101397 96474.2262810512 4922.77371894875 14 97994 98326.3999195871 -332.399919587129 15 94044 94389.11813641 -345.118136410005 16 91159 91555.113130523 -396.113130523067 17 87239 87704.6233374812 -465.623337481185 18 89235 89703.7044533642 -468.704453364247 19 118647 117845.772628029 801.22737197089 20 125620 127761.537998258 -2141.53799825798 21 125154 125475.92083626 -321.920836260309 22 117529 119486.218281916 -1957.21828191556 23 109459 110229.333517975 -770.333517974723 24 108483 108092.668042252 390.331957748058 25 107137 107271.619819757 -134.619819757208 26 104699 103305.30513524 1393.69486475992 27 100804 100428.855794712 375.14420528803 28 96066 97795.7866541242 -1729.78665412424 29 91971 92003.6665251494 -32.6665251493687 30 93228 94182.4737242576 -954.47372425755 31 120144 122567.956055048 -2423.95605504792 32 127233 128506.074067552 -1273.07406755212 33 127166 126309.573889893 856.426110106535 34 118194 120771.076124286 -2577.07612428618 35 109940 110217.708812814 -277.70881281422 36 106683 107989.967478556 -1306.96747855567 37 102834 104784.426618019 -1950.42661801871 38 99882 98332.8608574674 1549.13914253261 39 96666 95047.2316277384 1618.76837226162 40 92540 93156.872132615 -616.87213261491 41 88744 88121.5113453721 622.488654627887 42 89321 90424.0899789227 -1103.08997892265 43 115870 116820.025296034 -950.02529603368 44 122401 123415.21156438 -1014.21156438046 45 122030 121018.498579832 1011.50142016841 46 113802 115442.722074415 -1640.72207441457 47 105791 105773.505002394 17.4949976061907 48 103076 103598.277304962 -522.277304961812 49 98658 100997.683701832 -2339.68370183161 50 96945 94064.2553939145 2880.7446060855 51 92497 92113.386475772 383.613524228058 52 90687 88901.0424991883 1785.95750081171 53 88796 86338.3739136037 2457.62608639625 54 90015 90629.9056220276 -614.905622027596 55 113228 117986.74739014 -4758.74739014011 56 118711 120499.859214844 -1788.85921484396 57 117460 117195.414722752 264.585277247563 58 106556 110890.555396165 -4334.55539616494 59 97347 98582.3318795824 -1235.33187958237 60 92657 94764.2323705198 -2107.23237051979 61 93118 90080.1897049738 3037.81029502621 62 89037 88579.115912196 457.884087803948 63 83570 84202.4301368743 -632.430136874304 64 81693 79848.9665254759 1844.0334745241 65 75956 77346.4914324739 -1390.49143247391 66 73993 76760.1513257628 -2767.15132576284 67 97088 95723.3323530559 1364.66764694414 68 102394 102503.882472388 -109.882472388155 69 96549 100407.271713753 -3858.27171375277 70 89727 90135.186238539 -408.186238539056 71 82336 82353.0623959294 -17.0623959294317 72 82653 79599.7177474176 3053.28225258237 73 82303 80295.025584142 2007.97441585804 74 79596 78167.0059579082 1428.99404209181 75 74472 75251.5873104586 -779.587310458592 76 73562 71113.6564049697 2448.3435950303 77 66618 69682.3948192778 -3064.39481927778 78 69029 67174.846472335 1854.15352766497 79 89899 89683.663848974 215.336151025942 80 93774 95210.2299627812 -1436.22996278122 81 90305 92115.9084799295 -1810.90847992947 82 83799 84634.4137413744 -835.413741374417 83 80320 77177.4683907398 3142.5316092602 84 82497 78247.514170416 4249.48582958392 Extrapolation Forecasts of Exponential Smoothing t Forecast 95% Lower Bound 95% Upper Bound 85 80865.7303344552 77154.2174457224 84577.243223188 86 77305.9268617513 71933.2007532139 82678.6529702888 87 73436.8917092681 66745.9445425358 80127.8388760004 88 70538.597352153 62627.2833483703 78449.9113559356 89 66990.4571450589 58042.1925030114 75938.7217871064 90 68031.4000161489 57533.4203067391 78529.3797255587 91 88779.3674212067 73558.2529477385 104000.481894675 92 94422.523672485 76648.7716942669 112196.275650703 93 93291.4938004606 74135.0657602118 112447.921840709 94 88125.5085616557 68462.6563425604 107788.360780751 95 81897.5117296015 62096.8385151165 101698.184944086 96 80188.0238679949 59597.0776471834 100778.970088806

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb/1aket1305876691.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb/1aket1305876691.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb/24zx81305876691.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb/24zx81305876691.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb/3cfvi1305876691.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/20/t1305876603nzk4u5dqdxnftlb/3cfvi1305876691.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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