Results 11 to 20 of about 761 (64)

Minimal penalty for Goldenshluger-Lepski method [PDF]

, 2016
This paper is concerned with adaptive nonparametric estimation using the Goldenshluger-Lepski selection method. This estimator selection method is based on pairwise comparisons between estimators with respect to some loss function.
Lacour, Claire, Massart, Pascal
core   +5 more sources

Optimal bandwidth selection for recursive Gumbel kernel density estimators

Dependence Modeling, 2019
In this paper, we propose a data driven bandwidth selection of the recursive Gumbel kernel estimators of a probability density function based on a stochastic approximation algorithm.
Slaoui Yousri
doaj   +1 more source

Marshall's lemma for convex density estimation

, 2007
Marshall's [Nonparametric Techniques in Statistical Inference (1970) 174--176] lemma is an analytical result which implies $\sqrt{n}$--consistency of the distribution function corresponding to the Grenander [Skand. Aktuarietidskr.
Duembgen, Lutz, Rufibach, Kaspar, Wellner, Jon A.   +2 more
core   +2 more sources

Estimating a Polya frequency function_2

, 2007
We consider the non-parametric maximum likelihood estimation in the class of Polya frequency functions of order two, viz. the densities with a concave logarithm. This is a subclass of unimodal densities and fairly rich in general.
Meyer, Mary, Pal, Jayanta Kumar, Woodroofe, Michael   +2 more
core   +1 more source

Complete monotonicity of multinomial probabilities and its application to Bernstein estimators on the simplex

, 2018
Let $d\in \mathbb{N}$ and let $\gamma_i\in [0,\infty)$, $x_i\in (0,1)$ be such that $\sum_{i=1}^{d+1} \gamma_i = M\in (0,\infty)$ and $\sum_{i=1}^{d+1} x_i = 1$.
Ouimet, Frédéric
core   +1 more source

Equivalence theory for density estimation, Poisson processes and Gaussian white noise with drift [PDF]

, 2004
This paper establishes the global asymptotic equivalence between a Poisson process with variable intensity and white noise with drift under sharp smoothness conditions on the unknown function.
Brown, Lawrence D., Carter, Andrew V., Low, Mark G., Zhang, Cun-Hui   +3 more
core   +5 more sources

Local polynomial regression for circular predictors

, 2009
We consider local smoothing of datasets where the design space is the d-dimensional (d >= 1) torus and the response variable is real-valued. Our purpose is to extend least squares local polynomial fitting to this situation.
Agnese Panzera, Bai, Beran, Charles C. Taylor, Cogburn, Hall, Jammalamadaka, Klemelä, Lejeune, Marco Di Marzio, Mardia, Ruppert, Silverman   +12 more
core   +4 more sources

Estimation for spatial semi-functional partial linear regression model with missing response at random

Demonstratio Mathematica
The aim of this article is to study a semi-functional partial linear regression model (SFPLR) for spatial data with responses missing at random (MAR).
Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi   +3 more
doaj   +1 more source

Asymptotically minimax Bayes predictive densities

, 2007
Given a random sample from a distribution with density function that depends on an unknown parameter $\theta$, we are interested in accurately estimating the true parametric density function at a future observation from the same distribution.
Aslan, Mihaela
core   +1 more source

Likelihood approach for marginal proportional hazards regression in the presence of dependent censoring [PDF]

, 2005
In many public health problems, an important goal is to identify the effect of some treatment/intervention on the risk of failure for the whole population. A marginal proportional hazards regression model is often used to analyze such an effect.
Zeng, Donglin
core   +3 more sources