bayesian variable selection for random intercept modeling of gaussian and non

bayesian variable selection for random intercept modeling of gaussian and non

ID：7288295

大?。?42.77 KB

頁數(shù)：43頁

時間：2018-02-10

bayesian variable selection for random intercept modeling of gaussian and non_第1頁
bayesian variable selection for random intercept modeling of gaussian and non_第2頁
bayesian variable selection for random intercept modeling of gaussian and non_第3頁
bayesian variable selection for random intercept modeling of gaussian and non_第4頁
bayesian variable selection for random intercept modeling of gaussian and non_第5頁
資源描述：

《bayesian variable selection for random intercept modeling of gaussian and non》由會員上傳分享，免費在線閱讀，更多相關(guān)內(nèi)容在工程資料-天天文庫。

1、BayesianVariableSelectionforRandomInterceptModelingofGaussianandNon‐GaussianDataUniversityPressScholarshipOnlineOxfordScholarshipOnlineBayesianStatistics9JoséM.Bernardo,M.J.Bayarri,JamesO.Berger,A.P.Dawid,DavidHeckerman,AdrianF.M.Smith,andMikeWestPrintpublicationdate:2011PrintISBN-13:97801

2、99694587PublishedtoOxfordScholarshipOnline:January2012DOI:10.1093/acprof:oso/9780199694587.001.0001BayesianVariableSelectionforRandomInterceptModelingofGaussianandNon‐GaussianDataSylviaFrühwirth‐SchnatterHelgaWagnerDOI:10.1093/acprof:oso/9780199694587.003.0006AbstractandKeywordsThepaperdem

3、onstratesthatBayesianvariableselectionforrandominterceptmodelsiscloselyrelatedtotheappropriatechoiceofthedistributionofheterogeneity.If,forinstance,aLaplaceratherthananormalpriorisconsidered,weobtainaBayesianLassorandomeffectsmodelwhichallowsbothsmoothingand,additionally,individualshrinkag

4、eoftherandomeffectstoward0.Inaddition,westudyspike‐and‐slabrandomeffectsmodelswithbothanabsolutelycontinuousandaDiracspikeandprovidedetailsofMCMCestimationforallmodels.Simulationstudiescomparingthevariouspriorsshowthatthespike‐and‐slabrandomeffectsmodeloutperformsunimodal,non‐Gaussianprior

5、sasfarascorrectclassificationofnon‐zerorandomeffectsisconcernedandthatthereissurprisinglylittledifferencebetweenanabsolutelycontinuousandaDiracspike.ThePage1of43BayesianVariableSelectionforRandomInterceptModelingofGaussianandNon‐GaussianDatachoiceofappropriatecomponentdensities,however,isc

6、rucialandwewerenotabletoidentifyauniformlybestdistributionfamily.ThepaperconcludeswithanapplicationtoANOVAforbinomialdatausingalogitmodelwitharandomintercept.Keywords:BayesianLasso,MCMC,spike‐and‐slabpriors,shrinkageSummaryThepaperdemonstratesthatBayesianvariableselectionforrandomintercept

7、modelsiscloselyrelatedtotheappropriatechoiceofthedistributionofheterogeneity.If,forinstance,aLaplaceratherthananormalpriorisconsidered,weobtainaBayesianLassorandomeffectsmodelwhichallowsbothsmoothingand,additionally,individualshrinkageoftherandomeffectstoward0

當(dāng)前文檔最多預(yù)覽五頁，下載文檔查看全文

此文檔下載收益歸作者所有

當(dāng)前文檔最多預(yù)覽五頁，下載文檔查看全文
溫馨提示：
1. 部分包含數(shù)學(xué)公式或PPT動畫的文件，查看預(yù)覽時可能會顯示錯亂或異常，文件下載后無此問題，請放心下載。
2. 本文檔由用戶上傳，版權(quán)歸屬用戶，天天文庫負(fù)責(zé)整理代發(fā)布。如果您對本文檔版權(quán)有爭議請及時聯(lián)系客服。
3. 下載前請仔細(xì)閱讀文檔內(nèi)容，確認(rèn)文檔內(nèi)容符合您的需求后進(jìn)行下載，若出現(xiàn)內(nèi)容與標(biāo)題不符可向本站投訴處理。
4. 下載文檔時可能由于網(wǎng)絡(luò)波動等原因無法下載或下載錯誤，付費完成后未能成功下載的用戶請聯(lián)系客服處理。