39 citations · 40 across the 10 of their papers we have counts for
8 papers · 1 filter
Exact Bayesian inference for level-set Cox processes with piecewise constant intensity function
Flavio B. Gonçalves, Barbara C. C. Dias
This paper proposes a new methodology to perform Bayesian inference for a class of multidimensional Cox processes in which the intensity function is piecewise constant. Poisson pro…
Exact Bayesian inference for diffusion driven Cox processes
Flavio B. Gonçalves, Krzysztof G. Łatuszyński, Gareth O. Roberts
In this paper, we present a novel methodology to perform Bayesian inference for Cox processes in which the intensity function is driven by a diffusion process. The novelty lies in…
Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes
Flavio B. Gonçalves, Livia M. Dutra, Roger W. C. Silva
Statistical modeling of point patterns is an important and common problem in several areas. The Poisson process is the most common process used for this purpose, in particular, its…
Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves
Flávio B. Gonçalves, Juliane Venturelli, Rosangela H. Loschi
Most Item Response Theory (IRT) models for dichotomous responses are based on probit or logit link functions which assume a symmetric relationship between the probability of a corr…
Bayesian linear regression models with flexible error distributions
Nívea B. da Silva, Marcos O. Prates, Flávio B. Gonçalves
This work introduces a novel methodology based on finite mixtures of Student-t distributions to model the errors' distribution in linear regression models. The novelty lies on a pa…
Exact Monte Carlo likelihood-based inference for jump-diffusion processes
Flávio B. Gonçalves, Krzysztof G. Łatuszyński, Gareth O. Roberts
Statistical inference for discretely observed jump-diffusion processes is a complex problem which motivates new methodological challenges. Thus existing approaches invariably resor…
Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures
Flávio B Gonçalves, Marcos O. Prates, Victor H. Lachos
In this paper we present a novel methodology to perform Bayesian model selection in linear models with heavy-tailed distributions. We consider a finite mixture of distributions to…
Exact Bayesian inference in spatio-temporal Cox processes driven by multivariate Gaussian processes
Flávio B. Gonçalves, Dani Gamerman
In this paper we present a novel inference methodology to perform Bayesian inference for spatiotemporal Cox processes where the intensity function depends on a multivariate Gaussia…