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Article Dans Une Revue Computational Statistics and Data Analysis Année : 2013

Least-squares estimation of a convex discrete distribution

Résumé

The least squares estimator of a discrete distribution under the constraint of convexity is introduced. Its existence and uniqueness are shown and consistency and rate of convergence are established. Moreover it is shown that it always outperforms the classical empirical estimator in terms of the Euclidean distance. Results are given both in the well- and the mis-specified cases. The performance of the estimator is checked throughout a simulation study. An algorithm, based on the support reduction algorithm, is provided. Application to the estimation of species abundance distribution is discussed.

Dates et versions

hal-01019893 , version 1 (07-07-2014)

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Cécile Durot, Sylvie Huet, François Koladjo, Stephane Robin. Least-squares estimation of a convex discrete distribution. Computational Statistics and Data Analysis, 2013, 67, pp.282-298. ⟨10.1016/j.csda.2013.04.019⟩. ⟨hal-01019893⟩
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