Work

Fitting a Multi-modal Density by Dynamic Programming

Year: 2022

Type: preprint

Abstract: We consider the problem of fitting a probability density function when it is constrained to have a given number of modal intervals. We propose a dynamic programming approach to solving this problem numerically. When this number is not known, we provide several data-driven ways for selecting it. We perform some numerical experiments to illustrate our methodology.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2207.11121

Authors: Arias-Castro, Ery, Jiang, He

Institutions: University of California San Diego, California State Polytechnic University

Language: English

Topic: Bayesian Methods and Mixture Models

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4288044294

Cites:

Cited by: 1

Related to: 10