Add to ORKGIn this paper we focus on the problem of estimating a boundeddensity using a finite combination of densities from a givenclass. We consider the Maximum Likelihood Procedure (MLE) and the greedy procedure described by Li and Barron. Approximation and estimation bounds are given for the above methods. We extend and improve upon the estimation results of Li and Barron, and in particular prove an $O(\frac{1}{\sqrt{n}})$ bound on the estimation error which does not depend on the number of densities in the estimated combination
In this paper we prove the optimality of an aggregation procedure. We prove lower bounds for aggrega...
This thesis studies two types of research problems under finite mixture models. The first type is mi...
We propose a framework for nonparametric maximum likelihood estimation of densities in situations wh...
In this paper we focus on the problem of estimating a bounded density using a finite combination of ...
In this paper we focus on the problem of estimating a bounded density using a finite combination of ...
peer reviewedWe observe a n-sample, the distribution of which is assumed to belong, or at least to b...
An often-cited fact regarding mixing or mixture distributions is that their density functions are ab...
Abstract. The problem of estimating the parameters which determine a mixture density has been the su...
We study the rates of convergence of the maximum likelihood esti-mator (MLE) and posterior distribut...
This paper concerns estimation of mixture densities. It is the continuation of the work of Pommeret ...
Abstract. In this note, we give necessary and sufficient conditions for a maximum-likelihood estimat...
A comprehensive methodology for semiparametric probability density estimation is introduced and expl...
The mixture model for generating document is a generative language model used in information retriev...
We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dir...
Abst rac t. We consider maximum likelihood estimation of finite mixture of uniform distributions. We...
In this paper we prove the optimality of an aggregation procedure. We prove lower bounds for aggrega...
This thesis studies two types of research problems under finite mixture models. The first type is mi...
We propose a framework for nonparametric maximum likelihood estimation of densities in situations wh...
In this paper we focus on the problem of estimating a bounded density using a finite combination of ...
In this paper we focus on the problem of estimating a bounded density using a finite combination of ...
peer reviewedWe observe a n-sample, the distribution of which is assumed to belong, or at least to b...
An often-cited fact regarding mixing or mixture distributions is that their density functions are ab...
Abstract. The problem of estimating the parameters which determine a mixture density has been the su...
We study the rates of convergence of the maximum likelihood esti-mator (MLE) and posterior distribut...
This paper concerns estimation of mixture densities. It is the continuation of the work of Pommeret ...
Abstract. In this note, we give necessary and sufficient conditions for a maximum-likelihood estimat...
A comprehensive methodology for semiparametric probability density estimation is introduced and expl...
The mixture model for generating document is a generative language model used in information retriev...
We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dir...
Abst rac t. We consider maximum likelihood estimation of finite mixture of uniform distributions. We...
In this paper we prove the optimality of an aggregation procedure. We prove lower bounds for aggrega...
This thesis studies two types of research problems under finite mixture models. The first type is mi...
We propose a framework for nonparametric maximum likelihood estimation of densities in situations wh...