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作者：Gilbert, PB
作者单位：Harvard University; Harvard T.H. Chan School of Public Health
摘要：Vardi [Ann. Statist. 13 178-203 (1985)] introduced an s-sample biased sampling model with known selection weight functions, gave a condition under which the common underlying probability distribution G is uniquely estimable and developed simple procedure for computing the nonparametric maximum likelihood estimator (NPMLE) G(n) of G. Gill, Vardi and Wellner thoroughly described the large sample properties of Vardi's NPMLE, giving results on uniform consistency, convergence of root n (G(n) - G) ...
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作者：Arcones, MA; Samaniego, FJ
作者单位：State University of New York (SUNY) System; Binghamton University, SUNY; University of California System; University of California Davis
摘要：We identify the asymptotic behavior of the estimators proposed by Rojo and Samaniego and Mukejee of a distribution F assumed to be uniformly stochastically smaller than a known baseline distribution G. We show that these estimators are root n-convergent to a limit distribution with mean squared error smaller than or equal to the mean squared error of the empirical survival function. By examining the mean squared error of the limit distribution, we are able to identify the optimal estimator wit...
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作者：Stephens, M
作者单位：University of Oxford
摘要：Richardson and Green present a method of performing a Bayesian analysis of data from a finite mixture distribution with an unknown number of components. Their method is a Markov Chain Monte Carlo (MCMC) approach, which makes use of the reversible jump methodology described by Green. We describe an alternative MCMC method which views the parameters of the model as a (marked point process, extending methods suggested by Ripley to create a Markov birth-death process with an appropriate stationary...
