Print Email Facebook Twitter Current Status Censoring Models: Smooth estimators and their asymptotic properties Title Current Status Censoring Models: Smooth estimators and their asymptotic properties Author Witte, B.I. Contributor Groeneboom, P. (promotor) Jongbloed, G. (promotor) Faculty Electrical Engineering, Mathematics and Computer Science Department Statistics and Probability Date 2011-03-15 Abstract Statistics deals with answering questions based on collected data. In medical applications, the quantity of interest can often not be observed directly. They are censored. It is a challenge to answer the question as precisely as possible based on the incomplete data. The quantity of interest can be censored in many different ways. In HIV vaccine trials, censoring results in “current status continuous mark” data. This is a very specific type of censoring and the method of maximum likelihood that usually works very well does not work in this case. Hence, alternative methods are needed. In this thesis, different alternative methods are introduced and studied from different perspectives. Subject statisticscurrent status censoringdensity estimationkernel smoothinghistogram estimationasymptotic propertiesKullback-Leibler divergence To reference this document use: http://resolver.tudelft.nl/uuid:2e3da432-3d1c-4f2e-be8f-d250f2094e42 Publisher BOXPress ISBN 9789088912337 Part of collection Institutional Repository Document type doctoral thesis Rights (c) 2011 Witte, B.I. Files PDF proefschrift.pdf 4.14 MB Close viewer /islandora/object/uuid:2e3da432-3d1c-4f2e-be8f-d250f2094e42/datastream/OBJ/view