A Computational Approach to Log-Concave Density Estimation

Open access

Abstract

Non-parametric density estimation with shape restrictions has witnessed a great deal of attention recently. We consider the maximum-likelihood problem of estimating a log-concave density from a given finite set of empirical data and present a computational approach to the resulting optimization problem. Our approach targets the ability to trade-off computational costs against estimation accuracy in order to alleviate the curse of dimensionality of density estimation in higher dimensions.

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Analele Universitatii "Ovidius" Constanta - Seria Matematica

The Journal of "Ovidius" University of Constanta

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CiteScore 2017: 0.59

SCImago Journal Rank (SJR) 2017: 0.316
Source Normalized Impact per Paper (SNIP) 2017: 0.790

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researchers in all fields of pure and applied mathematics

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