Limit distribution theory for maximum likelihood estimation of a log-concave density

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Abstract

We find limiting distributions of the nonparametric maximum likelihood estimator (MLE) of a log-concave density, that is, a density of the form f0 = expφ0 where φ0 is a concave function on R. The pointwise limiting distributions depend on the second and third derivatives at 0 of Hk, the "lower invelope" of an integrated Brownian motion process minus a drift term depending on the number of vanishing derivatives of φ0 = log f0 at the point of interest. We also establish the limiting distribution of the resulting estimator of the mode M(f0) and establish a new local asymptotic minimax lower bound which shows the optimality of our mode estimator in terms of both rate of convergence and dependence of constants on population values.

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Balabdaoui, F., Rufibach, K., & Wellner, J. A. (2009). Limit distribution theory for maximum likelihood estimation of a log-concave density. Annals of Statistics, 37(3), 1299–1331. https://doi.org/10.1214/08-AOS609

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