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20242026
most citedTweedie-based nonparametric estimation for semicontinuous mixed densities

1 citations · 1 across the 12 of their papers we have counts for

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24 papers

math.PR2026

On a conjecture of Lamkin and Tkocz: Log-convexity of moments of Bernoulli sample means

Frédéric Ouimet, Frédéric Ouimet

Let be independent random variables, and let . We prove that, for every real , the sequenc…

math.PR2026

Log-convexity and log-concavity of noncentral gamma sums and differences

Robert E. Gaunt, Frédéric Ouimet

We study log-convexity and log-concavity of densities obtained from sums and differences of two independent noncentral gamma random variables. We give a complete classification of…

math.PR2026

On Wilks' problem: Exact recursive formulas via Stein's method for the joint moments of disjoint principal minors of Wishart random matrices

Robert E. Gaunt, Frédéric Ouimet

In a 1934 Annals of Mathematics paper, Samuel S. Wilks posed the problem of computing joint moments of disjoint principal minors of Wishart random matrices, describing the general…

math.ST2026

On the Dirichlet-kernel Gasser--Müller estimator and its competitors for fixed design regression on the simplex

Hanen Daayeb, Christian Genest, Salah Khardani +2

A Dirichlet-kernel Gasser-Müller (D-GM) estimator is introduced for fixed design regression on the simplex, extending the univariate analog due to Chen [Statist. Sinica, vol. 10(1…

math.PR2026

Stein's method for the symmetric matrix normal distribution with an application to the approximation of the Wishart law

Robert E. Gaunt, Frédéric Ouimet

In this paper, we extend Stein's method to the symmetric matrix normal distribution. In particular, we obtain a Stein characterization of the symmetric matrix normal distribution i…

stat.ME2026

Dirichlet kernel density estimation on the simplex with missing data

Sami Baraket, Hanen Daayeb, Salah Khardani +2

Nonparametric density estimation for compositional data supported on the simplex is examined under a missing at random mechanism. Rather than imputing missing values and estimating…