Comparing two populations using Bayesian Fourier series density estimation

Autor(es)

de Almeida Inacio, Marco Henrique ^{[1, 2]} ; Izbicki, Rafael ^[2] ; Salasar, Luis Ernesto ^[2]

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION; v. 49, n. 1, p. 261-282, JAN 2 2020.
• Citações Web of Science: 0

Resumo

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)

• Processo FAPESP: 14/25302-2 - Uma abordagem flexível para a estimação de uma densidade condicional em problemas com alta dimensionalidade
• Beneficiário: Rafael Izbicki
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/03363-8 - Interpretabilidade e eficiência em testes de hipótese
• Beneficiário: Rafael Izbicki
• Modalidade de apoio: Auxílio à Pesquisa - Regular