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Workshop “Frontiers of High Dimensional Statistics, Optimization, and Econometrics”
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[Simultaneous likelihood-based bootstrap confidence sets for misspecified models] М. М. Жилова Московский физико-технический институт (государственный университет), г. Долгопрудный Московской обл. |
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Аннотация: We consider a multiplier bootstrap procedure for construction of likelihood-based confidence sets for finite samples and a possible model misspecification. The approach is also generalized for the case of simultaneous confidence sets, when the number of parametric models is allowed to be exponentially large w.r.t. the sample size. Theoretical results justify the bootstrap consistency for a fixed sample size. Good numerical performance of the bootstrap procedure is demonstrated with experiments for misspecified regression models. Язык доклада: английский |
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