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A practical implementation of weighted kernel density estimation for handling shape constraints

Mark Anthony Wolters | Willard John Braun | Mark A. Wolters | W. J. Braun

[1] Dávid Papp,et al. Shape-Constrained Estimation Using Nonnegative Splines , 2014 .

[2] Peter Hall,et al. Attributing a probability to the shape of a probability density , 2004 .

[3] L. Ahrens,et al. Observations on the Fe-Si-Mg relationship in chondrites , 1965 .

[4] I. Good,et al. Density Estimation and Bump-Hunting by the Penalized Likelihood Method Exemplified by Scattering and Meteorite Data , 1980 .

[5] L. Dümbgen,et al. logcondens: Computations Related to Univariate Log-Concave Density Estimation , 2011 .

[6] Michael C. Minnotte,et al. Nonparametric testing of the existence of modes , 1997 .

[7] R. Samworth. Recent Progress in Log-Concave Density Estimation , 2017, Statistical Science.

[8] L. Duembgen,et al. Maximum likelihood estimation of a log-concave density and its distribution function: Basic properties and uniform consistency , 2007, 0709.0334.

[9] Melanie Birke,et al. Shape constrained kernel density estimation , 2009 .

[10] Johannes O. Royset,et al. Fusion of hard and soft information in nonparametric density estimation , 2015, Eur. J. Oper. Res..

[11] Bradley C. Turnbull,et al. Unimodal density estimation using Bernstein polynomials , 2014, Comput. Stat. Data Anal..

[12] Eckhard Platen,et al. On the Distributional Characterization of Daily Log‐Returns of a World Stock Index , 2006 .

[13] M. Cule,et al. Maximum likelihood estimation of a multi‐dimensional log‐concave density , 2008, 0804.3989.