Variational methods have been proposed for obtaining deterministic lower bounds for log-likelihoods within missing data problems, but with little formal justification or investigation of the worth of the lower bound surfaces as tools for inference. We provide, within a general Markovian context,...

Local polynomial methods hold considerable promise for boundary estimation, where they offer unmatched flexibility and adaptivity. Most rival techniques provide only a single order of approximation; local polynomial approaches allow any order desired. Their more conventional rivals, for example...

We show that the bootstrap approximation to the distribution of the Studentized trimmed mean performs better than the normal approximation, in that it is in error by terms of smaller order than n-1/2, where n denotes sample size. No assumptions are made about symmetry and only mild smoothness...

We describe a class of smoothed orthogonal series density estimates, including the classical sequential-series introduced by [6], Soviet Math. Dokl. 3 1559-1562) and [16], Ann. Math. Statist. 38 1261-1265), and [23], Ann. Statist 9 146-156) two-parameter smoothing. The Bowman-Rudemo method of...