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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Comparing two populations using Bayesian Fourier series density estimation

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Author(s):
de Almeida Inacio, Marco Henrique [1, 2] ; Izbicki, Rafael [2] ; Salasar, Luis Ernesto [2]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Paulo, SP - Brazil
[2] Fed Univ Sao Carlos UFSCar, Dept Stat, Rodovia Washington Lus, Km 235, SP-310, Sao Carlos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION; v. 49, n. 1, p. 261-282, JAN 2 2020.
Web of Science Citations: 0
Abstract

An important question in sciences is how to evaluate the similarity between two populations given independent samples from each of them. The most common approach to solve this is to use standard hypotheses tests. We propose an alternative method to compare two groups using a Bayesian nonparametric framework. The key idea is to measure the similarity between them by evaluating the distance between their associated densities. The nonparametric perspective makes it straightforward to assess the uncertainty about such distance without making strong assumptions about the generating processes. We provide both simulated and real examples to illustrate our method effectiveness. (AU)

FAPESP's process: 14/25302-2 - A flexible approach to high-dimensional conditional density estimation
Grantee:Rafael Izbicki
Support Opportunities: Regular Research Grants
FAPESP's process: 17/03363-8 - Interpretability and efficiency in hypothesis tests
Grantee:Rafael Izbicki
Support Opportunities: Regular Research Grants