26 citations · 305 across the 66 of their papers we have counts for
7 papers · 2 filters
A study of seven asymmetric kernels for the estimation of cumulative distribution functions
Pierre Lafaye de Micheaux, Frédéric Ouimet
In Mombeni et al. (2019), Birnbaum-Saunders and Weibull kernel estimators were introduced for the estimation of cumulative distribution functions (c.d.f.s) supported on the half-li…
An improvement of Tusnády's inequality in the bulk
Frédéric Ouimet
We prove a non-asymptotic generalization of the refined continuity correction developed in Cressie (1978) for the Binomial distribution, which we then use to improve the versions o…
On the Le Cam distance between Poisson and Gaussian experiments and the asymptotic properties of Szasz estimators
Frédéric Ouimet
In this paper, we prove a local limit theorem for the ratio of the Poisson distribution to the Gaussian distribution with the same mean and variance, using only elementary methods…
On the boundary properties of Bernstein estimators on the simplex
Frédéric Ouimet
In this paper, we study the asymptotic properties (bias, variance, mean squared error) of Bernstein estimators for cumulative distribution functions and density functions near and…
Asymptotic properties of Bernstein estimators on the simplex
Frédéric Ouimet
Bernstein estimators are well-known to avoid the boundary bias problem of traditional kernel estimators. The theoretical properties of these estimators have been studied extensivel…
Asymptotic properties of Dirichlet kernel density estimators
Frédéric Ouimet, Raimon Tolosana-Delgado
We study theoretically, for the first time, the Dirichlet kernel estimator introduced by Aitchison and Lauder (1985) for the estimation of multivariate densities supported on the $…
A precise local limit theorem for the multinomial distribution and some applications
Frédéric Ouimet
In Siotani & Fujikoshi (1984), a precise local limit theorem for the multinomial distribution is derived by inverting the Fourier transform, where the error terms are explicit up t…