opdracht 10 reeks bouwvergunningen vlaanderen GILLES HEYMANS

*Unverified author*

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

Title produced by software: Exponential Smoothing

Date of computation: Thu, 04 Jun 2009 10:41:39 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe.htm/, Retrieved Thu, 04 Jun 2009 18:42:23 +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/2009/Jun/04/t1244133739ammw1alw4p9m6xe.htm/}, year = {2009}, } @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 = {2009}, 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 «

1639 1296 1063 1282 1365 1268 1532 1455 1393 1515 1510 1225 1577 1417 1224 1693 1633 1639 1914 1586 1552 2081 1500 1437 1470 1849 1387 1592 1590 1798 1935 1887 2027 2080 1556 1682 1785 1869 1781 2082 2571 1862 1938 1505 1767 1607 1578 1495 1615 1700 1337 1531 1623 1543 1638 1520 1416 1820 1596 1358 1267 1742 1402 1388 1646 1670 1531 1730 1407 1795 1504 1371 1734

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Estimated Parameters of Exponential Smoothing Parameter Value alpha 0.352262650278532 beta 0.0394175072825745 gamma 0.365382321391222 Interpolation Forecasts of Exponential Smoothing t Observed Fitted Residuals 13 1577 1422.81387939779 154.186120602207 14 1417 1331.20941435374 85.79058564626 15 1224 1187.11669176298 36.8833082370209 16 1693 1656.23575532492 36.7642446750838 17 1633 1613.95404382272 19.0459561772764 18 1639 1645.68117630928 -6.68117630927736 19 1914 1811.03043214306 102.969567856944 20 1586 1780.99226298622 -194.992262986224 21 1552 1651.07540872186 -99.075408721861 22 2081 1753.98738221983 327.012617780174 23 1500 1856.20734017917 -356.207340179170 24 1437 1398.36727627767 38.6327237223311 25 1470 1849.85618427538 -379.856184275382 26 1849 1524.11506748975 324.884932510254 27 1387 1413.11422752116 -26.1142275211616 28 1592 1926.29251852413 -334.292518524129 29 1590 1734.92099272508 -144.920992725083 30 1798 1692.85946261665 105.140537383350 31 1935 1922.94709619176 12.0529038082445 32 1887 1774.29703580103 112.702964198969 33 2027 1764.41182777473 262.588172225274 34 2080 2125.29026122948 -45.2902612294765 35 1556 1906.43956399688 -350.439563996882 36 1682 1518.47972615291 163.520273847091 37 1785 1938.57812999022 -153.578129990216 38 1869 1846.12639825767 22.8736017423312 39 1781 1515.59035384715 265.409646152848 40 2082 2117.50656024182 -35.5065602418181 41 2571 2068.91233938390 502.087660616095 42 1862 2345.11581640973 -483.115816409728 43 1938 2387.90559531103 -449.905595311028 44 1505 2076.310187768 -571.310187767998 45 1767 1847.5662682562 -80.5662682562017 46 1607 1990.12611110514 -383.126111105142 47 1578 1592.03715579472 -14.0371557947151 48 1495 1441.67742403766 53.3225759623408 49 1615 1705.98573198027 -90.9857319802734 50 1700 1664.20662138857 35.7933786114277 51 1337 1409.49035316494 -72.4903531649375 52 1531 1729.06988679182 -198.069886791816 53 1623 1705.34642216078 -82.3464221607842 54 1543 1553.87141847292 -10.8714184729201 55 1638 1690.90420118187 -52.9042011818683 56 1520 1502.72673526084 17.2732647391574 57 1416 1575.30879091192 -159.308790911922 58 1820 1585.80816987033 234.191830129669 59 1596 1497.88486903714 98.1151309628558 60 1358 1404.46920867185 -46.4692086718483 61 1267 1582.58290319862 -315.582903198624 62 1742 1482.07714849129 259.922851508711 63 1402 1296.1752086595 105.8247913405 64 1388 1637.55704132813 -249.557041328128 65 1646 1617.28025357423 28.7197464257747 66 1670 1522.64508947200 147.354910528001 67 1531 1708.82828933741 -177.828289337413 68 1730 1494.00592772033 235.994072279667 69 1407 1604.05086529555 -197.050865295548 70 1795 1699.6121454973 95.3878545027019 71 1504 1529.12219285863 -25.1221928586297 72 1371 1360.29033584682 10.7096641531773 73 1734 1487.38376998273 246.616230017269 Extrapolation Forecasts of Exponential Smoothing t Forecast 95% Lower Bound 95% Upper Bound 74 1743.82695065321 1494.74826689777 1992.90563440864 75 1411.40846241099 1132.71521355902 1690.10171126296 76 1638.32218706025 1296.61969885395 1980.02467526654 77 1790.84633772720 1390.15387705781 2191.53879839660 78 1710.71092842501 1286.54476323048 2134.87709361954 79 1772.92748552079 1300.89722760145 2244.95774344013 80 1715.12889686094 1220.39098666354 2209.86680705834 81 1635.23282896538 1124.78145908473 2145.68419884604 82 1897.32214560113 1282.22246638975 2512.42182481251 83 1649.17545123005 1071.32408523573 2227.02681722437 84 1487.43742457432 925.241957905221 2049.63289124341 85 1682.42471987237 1067.51241811790 2297.33702162685

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe/1ga361244133697.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe/1ga361244133697.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe/27w3d1244133697.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe/27w3d1244133697.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe/3dua71244133697.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244133739ammw1alw4p9m6xe/3dua71244133697.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=0, beta=0) if (par2 == 'Double') fit <- HoltWinters(x, gamma=0) 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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