Complexity penalized support estimation

Jussi Klemelä

Journal of Multivariate Analysis, 2004, vol. 88, issue 2, 274-297

Abstract: We consider the estimation of the support of a probability density function with iid observations. The estimator to be considered is a minimizer of a complexity penalized excess mass criterion. We present a fast algorithm for the construction of the estimator. The estimator is able to estimate supports which consists of disconnected regions. We will prove that the estimator achieves minimax rates of convergence up to a logarithmic factor simultaneously over a scale of Hölder smoothness classes for the boundary of the support. The proof assumes a sharp boundary for the support.

Keywords: Adaptive; estimation; Data-dependent; partitions; Quality; control; Multivariate; data; Tree; structured; estimators (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (2)

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