Penalized Likelihood-type Estimators for Generalized Nonparametric Regression

Dennis D. Cox and Finbarr O'Sullivan

Journal of Multivariate Analysis, 1996, vol. 56, issue 2, 185-206

Abstract: We consider the asymptotic analysis of penalized likelihood type estimators for generalized nonparametric regression problems in which the target parameter is a vector-valued function defined in terms of the conditional distribution of a response given a set of covariates. A variety of examples including ones related to generalized linear models and robust smoothing are covered by the theory. Linear approximations to the estimator are constructed using Taylor expansions in Hilbert spaces. An application which is treated is upper bounds on rates of convergence for the penalized likelihood-type estimators.

Keywords: maximum; penalized; likelihood; non-parametric; aggression; multiple; classification; smoothing; splines; rates; of; convergence; (null) (search for similar items in EconPapers)
Date: 1996
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Citations: View citations in EconPapers (2)

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