Work

Adaptive non-asymptotic confidence balls in density estimation

Year: 2010

Type: preprint

Abstract: We build confidence balls for the common density $s$ of a real valued sample $X_1,...,X_n$. We use resampling methods to estimate the projection of $s$ onto finite dimensional linear spaces and a model selection procedure to choose an optimal approximation space. The covering property is ensured for all $n\geq2$ and the balls are adaptive over a collection of linear spaces.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1007.4528

Author: Lerasle, Matthieu

Institutions: Universidade de São Paulo, Institut National des Sciences Appliquées de Toulouse, Université de Toulouse, Institut de Mathématiques de Toulouse

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2949689082

Cites: 9

Cited by:

Related to: 19