Efficient and Adaptive Estimation for Semiparametric Models (Johns Hopkins Studies in the Mathematical Sciences)

Originating with the 1983 Mathematical Sciences Lectures at Johns Hopkins given by Peter J. Bickel and Jon A. Wellner, this volume is about estimation in situations where enough is known to model some features of the data parametrically but not enough is known to assume anything for other features. Such models have arisen in a wide variety of contexts in recent years, particularly in economics, epidemiology, and astronomy. The focus is on asymptotic theory, and the scope is limited to models for independent, identically distributed observations. Annotation copyright Book News, Inc. Portland, Or.