Banca de DEFESA: KARINE DOS SANTOS ARAUJO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : KARINE DOS SANTOS ARAUJO
DATE: 17/03/2025
TIME: 14:00
LOCAL: Ambiente virtual
TITLE:

Bayesian inference for Poisson models with conjugate priors based on mixtures of the
Gamma distribution

KEY WORDS:

Bayesian inference; Gamma mixtures; Conjugate prior; Poisson Distribution

PAGES: 50
BIG AREA: Ciências Exatas e da Terra
AREA: Probabilidade e Estatística
SUMMARY:

Bayesian inference is a statistical methodology that combines prior information
about model parameters with observational data to estimate the posterior distribution of
unknown parameters. One of the advantages of using conjugate priors is that the resulting
posterior distribution remains within the same family of distributions as the prior, which
facilitates both the calculations and the intuitive interpretation of the posterior parameters. In
this study, we adopted mixtures of Gamma distributions as conjugate priors for the λ
parameter of the Poisson distribution, which provides a more flexible approach capable of
better adjusting to different data characteristics. The mixtures of Gamma distributions
explored in this work include the generalized Lindley distribution 1 (ABOUAMMOH;

ALSHANGITI; RAGAB, 2015), the generalized Lindley distribution 2 (RAMOS; LOUZADA; MOALA,
2021) and the generalized Lindley distribution 3 (ZAKERZADEH; DOLATI, 2009). These
distributions are extensions of the classic Lindley distribution. To illustrate the practical
application of the proposed methodology, we carried out a study with real data.

COMMITTEE MEMBERS:
Presidente - 1023112 - MARCELO BOURGUIGNON PEREIRA
Interno - ***.629.298-** - FERNANDO FERRAZ DO NASCIMENTO - UFPI
Externo à Instituição - NELSON LIMA DE SOUZA FILHO - UFAM