We show that the density of Z=argmax{W(t)−t2}, sometimes known as Chernoff’s density, is log-concave. We conjecture that Chernoff’s density is strongly log-concave or “super-Gaussian”, and provide evidence in support of the conjecture
We show that both parametric distribution functions appearing in extreme value theory have log-conca...
We present theoretical properties of the log-concave maximum likelihood estimator of a density based...
Abstract. Given an isotropic random vector X with log-concave density in Eu-clidean space Rn, we stu...
In recent years, log-concave density estimation via maximum likelihood estimation has emerged as a f...
We study the problem of maximum likelihood estimation of densities that are log-concave and lie in t...
Interesting properties and propositions, in many branches of science such as economics have been ob...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
We show that both parametric distribution functions appearing in extreme value theory have log-conca...
Maximum likelihood estimation of a log-concave density has attracted considerable attention over the...
We study the adaptation properties of the multivariate log-concave maximum likelihood estimator over...
Publisher Copyright: © 2022 The Author(s)We study probability density functions that are log-concave...
AbstractA weak version of a conjecture stated by Kannan, Lovász and Simonovits claims that an isotro...
We show that both parametric distribution functions appearing in extreme value theory have log-conca...
We present theoretical properties of the log-concave maximum likelihood estimator of a density based...
Abstract. Given an isotropic random vector X with log-concave density in Eu-clidean space Rn, we stu...
In recent years, log-concave density estimation via maximum likelihood estimation has emerged as a f...
We study the problem of maximum likelihood estimation of densities that are log-concave and lie in t...
Interesting properties and propositions, in many branches of science such as economics have been ob...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
International audienceWe derive explicit bounds for the computation of normalizing constants Z for l...
We show that both parametric distribution functions appearing in extreme value theory have log-conca...
Maximum likelihood estimation of a log-concave density has attracted considerable attention over the...
We study the adaptation properties of the multivariate log-concave maximum likelihood estimator over...
Publisher Copyright: © 2022 The Author(s)We study probability density functions that are log-concave...
AbstractA weak version of a conjecture stated by Kannan, Lovász and Simonovits claims that an isotro...
We show that both parametric distribution functions appearing in extreme value theory have log-conca...
We present theoretical properties of the log-concave maximum likelihood estimator of a density based...
Abstract. Given an isotropic random vector X with log-concave density in Eu-clidean space Rn, we stu...