Publicações

1. FERNANDEZ, R. C., GONÇALVES, K. C. M. e PEREIRA, J. B. M. A flexible Bayesian hierarchical quantile spatial model for areal data. Statistical Modelling, v. 25, p. 35-54, 2025. (Publicado online em 2023.)

2. NOLAU, I., GONÇALVES, K. C. M. e PEREIRA, J. B. M. Model-based inference for rare and clustered populations from adaptive cluster sampling using auxiliary variables. Journal Of Survey Statistics And Methodology, v. 10, p. 439-465, 2022. (Publicado online em 2021.)

3. CAPDEVILLE, V., GONÇALVES, K. C. M. e PEREIRA, J. B. M. Bayesian factor models for multivariate categorical data obtained from questionnaires. Journal of Applied Statistics, v. 48, p. 3150-3173, 2021. (Publicado online em 2020.)

4. PEREIRA, J. B. M., NOBRE, W. S., SILVA, I. F. L. e SCHMIDT, A. M. Spatial confounding in hurdle multilevel beta models: the case of the Brazilian Mathematical Olympics for Public Schools. Journal of the Royal Statistical Society Series A - Statistics in Society, v. 183, p. 1051-1073, 2020. 

5. NOBRE, W. S., SCHMIDT, A. M., PEREIRA, J. B. M. On the effects of spatial confounding in hierarchical models. International Statistical Review, v. 89, p. 302-322, 2020.

6. SOUSA, M. A. O., MIGON, H. S. e PEREIRA, J. B. M. Extended dynamic generalized linear models: the two-parameter exponential family. Computational Statistics & Data Analysis, v. 121, p. 164-179, 2018.

7. FÚQUENE PATIÑO, J. A., BETANCOURT, B. e PEREIRA, J. B. M. A weakly informative prior for Bayesian dynamic model selection with applications in fMRI. Journal of Applied Statistics, v. 45, p. 1173-1192, 2018. (Publicado online em 2017.)

8. MIGON, H. S., SCHMIDT, A. M., RAVINES, R. E. R. e PEREIRA, J. B. M. An efficient sampling scheme for dynamic generalized models. Computational Statistics, v. 28, p. 2267-2293, 2013.

9. SCHMIDT, A. M. e PEREIRA, J. B. M. Modelling time series of counts in Epidemiology. International Statistical Review, v. 79, p. 48-69, 2011.

SCHMIDT, A. M., HOETING, J. e PEREIRA, J. B. M. Mapping malaria in the Amazon Rainforest: a spatio-temporal mixture model. In: Tony O'Hagan e Mike West (Org.). The Oxford Handbook of Applied Bayesian Analysis. Oxford Press, 2010, p. 90-115. 

Título: Modelos Baseados em Convoluções de Processos Aleatórios para Dados de Contagem Espacialmente Referenciados (2015).

Orientação: Alexandra M. Schmidt (McGill), Marco A. Rodriguez  (UQTR) e Bruno Sansó (UCSC).

Título: Modelos para Dados de Contagem com Estrutura Temporal. (2010).

Orientação: Alexandra M. Schmidt (McGill) e Helio S. Migon (UFRJ).