Publications

Published\Accepted papers and book chapters

2020 to present

• BayesMortalityPlus: A package in R for Bayesian mortality modelling (202*) L. M. F. Silva and L. F. V. Figueiredo and V. G. R. Lobo and T. C. O. Fonseca and M. B. Alves, Journal of Statistical Software, to appear.

• Ensembles of dynamic multiscale spatiotemporal models for smooth covariance functions (202*) M.A.R. Ferreira and T.C.O. Fonseca. Book chapter. Chaptan-Hall, to appear.

• Seguros de pessoas e de previdência complementar: diferenciais de mortalidade por nível educacional. (2024) A. Bertho; B. Costa; R. Peregrino; N. Fernandes; T. Fonseca. Revista Contabilidade & Finanças. To appear.

• An Implementation analysis of a quality improvement project to reduce cesarean section in Brazilian private hospitals (2023). J. Torres, T. Leite, T. C. O. Fonseca, R. Domingues, A. Figueiró, A. Pereira, R. Sanchez, P. Borem, M. Osti, M. Rosa, A. Andrade, B. Ayres, M. Nakamura-Pereira, F. Peixoto Filho, M. Leal. Reproductive Health (Springer Nature), 20:190 https://doi.org/10.1186/s12978-024-01773-6

• BR-EMS 2021 life table for the Brazilian insured population. (2023). M. Oliveira; A. Bertho; B. Costa; F. Silva; M. Alves; M. Ramirez; R. Borges; R. Marques; R. Peregrino; T. Fonseca; V. Lobo. REBEP. Revista Brasileira De Estudos De População, 40. https://doi.org/10.20947/S0102-3098a0252

• Lapse risk modeling in insurance: a Bayesian mixture approach. (2023) Lobo VGR, Fonseca TCO, Alves MB. Annals of Actuarial Science. 2023:1-26. doi:10.1017/S1748499523000180

• Dynamical non-Gaussian modelling of spatial processes (2023). T. C. O. Fonseca, V.G. Lobo, and A.M. Schmidt. Arxiv. Journal of the Royal Statistical Society (Series C - Applied), Volume 72, Issue 1, 76–103.

• An overview of non-Gaussian state-space models for wind speed data (2023). V. E. L. A. Duca, and T. C. O. Fonseca, and F. L. Cyrino Oliveira. Energy. DOI , Volume 266.

• The effects of a quality improvement project to reduce caesarean sections in selected private hospitals in Brazil. (2022) do Carmo Leal, M., Domingues, R.M.S.M., Fonseca, T.C.O. et al. Reprod Health 20 (Suppl 2), 194. https://doi.org/10.1186/s12978-024-01851-9 open access.

• Joint modelling wind speed and power via Bayesian Dynamical models. (2022) V. E. L. A. Duca, and T. C. O. Fonseca, and F. L. Cyrino Oliveira. Energy, Vol 247. https://doi.org/10.1016/j.energy.2022.123431 

• Safeguarding the Nation’s Digital Memory: Bayesian Network Modelling of Digital Preservation Risks (2022) M. J. Barons, T. C. O. Fonseca, H. Merwood and D. H. Underdown.(Chapter in the Book: Progress in Industrial Mathematics at ECMI 2021, Proceedings of the European Consortium for Mathematics in Industry 2021 (ECMI 2021, Springer). DOI

• A decision support system for addressing food security in the UK. (2021) M.J.Barons, T.C.O.Fonseca, A.Davis and J.Q.Smith. Journal of the Royal Statistical Society, Series A (Statistics in Society), 00, 1– 24, DOI: 10.1111/rssa.12771 (open access) Arxiv

• Space-time calibration of wind speed forecasts from regional climate models (2021). Gomes, L., Fonseca, T. C. O., Gonçalves, K. and Cardenas, R., Environmental and Ecological Statistics, 28 (3), 631-665, DOI: 10.1007/s10651-021-00509-0 Arxiv

• Calibração espaço-temporal de previsões numéricas do modelo de mesoescala ETA para a velocidade do vento em Minas Gerais. (2021) Gomes, L., Fonseca, T. C. O., Gonçalves, K. and Cardenas, R., Chapter in the book: Aplicações Avançadas de Simulação Computacional (portuguese). DOI:10.53268/BKF21060405

• Safeguarding the Nation’s Digital Memory: Towards a Bayesian Model of Digital Preservation Risk (2021) M J Barons, S Bhatia, T C O Fonseca, A Green, S Krol, H Merwood, A Mulinder, S Ranade, J Q Smith, T Thornhill, D H Underdown Archives and Records, 42:1, 58-78, DOI: 10.1080/23257962.2021.1873121    Open access link

• A Generalized Dynamical Model for Wind Speed Prediction (2021). V.E. L.A. Duca and T.C.O.Fonseca and F. L. C. Oliveira. Renewable and Sustainable Energy Reviews, volume 136, February 2021.

• Evaluating the performance of degrees  of  freedom  estimation   in Asymmetric GARCH  models  with  Student-t  innovations (2020). T. C. O. Fonseca, V. S. Cerqueira, H. S. Migon and C.A.C. Torres. Brazilian Review of Econometrics vol. 40, n. 2 pp. 347–373 November 2020, DOI: 10.12660/bre.v40n22020.80292 

• Bayesian cross-validation of geostatistical models (2020), V. G. Lobo, T. C. O. Fonseca and F. Moura, Spatial Statistics, Vol 35, March. DOI Arxiv

• Bayesian residual analysis for spatially correlated data (2020), Viviana G. Lobo, Thais C. O. Fonseca, Statistical Modelling, Vol 20, Issue 2, 171-194. DOI

Before 2020

• Covariance Modeling for Multivariate Spatial Processes Based on Separable Approximations. (2018), Erbisti R.S., Fonseca T.C.O., Alves M.B.  In: Bayesian Inference and Maximum Entropy Methods in Science and Engineering. maxent 2017. Springer, pp 243-252.

• Accounting for covariate information in the scale component of spatio-temporal mixing models (2017), R.S. Bueno, T.C.O.Fonseca and A.M.Schmidt, Spatial Statistics 22, 196-218. DOI 

• Dynamic Multiscale Spatiotemporal Models for Poisson Data (2017), T.C.O. Fonseca and M.A.R. Ferreira, Journal of the American Statistical Association 112:517, 215-234, DOI: 10.1080/01621459.2015.1129968

• Objective Bayesian analysis for the Student-t regression model (2014), Fonseca, T. C. O., Ferreira, M. A. R., and Migon, H. S. Biometrika, Volume 101, Issue 1, 1 March, Pages 252, DOI

• Bayesian analysis based on the Jeffreys prior for the hyperbolic distribution. (2012), Fonseca, T. C. O.,  Migon, H. S. and Ferreira, M. A. R., Brazilian Journal of Probability and Statistics, 26, 4, pages 327-343. DOI:10.1214/11-BJPS142

• Data mining for longitudinal data with different treatments (2011). M. Akacha, T.C.O. Fonseca and S. Liverani. Chapter in the Book: New perspectives in statistical modelling and data analysis,  pp 409-416, Springer.

• Non-Gaussian Spatiotemporal Modelling through Scale Mixing (2011). Fonseca, T. C. O. and Steel, M. F. J. Biometrika, 98, 4, 761–774.

• A General Class of Nonseparable Space-time Covariance Models (2011). Fonseca, T. C. O. and Steel, M. F. J. Environmetrics, 22, 2, 224–242

• Association between genital intraepithelial lesions and anal squamous intraepithelial lesions in HIV-negative women. Jacyntho CMA, Giraldo PC, Horta AA, R. Grandelle, A. K Gonçalves, T. C. O. Fonseca, José Eleutério Jr, Am J Obstet Gynecol (2011);205:115.e1-5.

• Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency (2009). A. M. Schmidt, A. R. B. Moreira,  S. M. Helfand, and T. C. O. Fonseca. Journal of Productivity Analysis, 31, 101-112. 

• Objective Bayesian analysis for the Student-t regression model (2008). Fonseca, T. C. O., Ferreira, M. A. R., and Migon, H. S. Biometrika, 95, 2, 325–333.

• A influência das doenças crônicas na capacidade funcional dos idosos do Município de São Paulo, Brasil (2007). L. C. Alves, B. C. Q. Leimann, M. E. L. Vasconcelos, M. Sá Carvalho, A. G. G. Vasconcelos, T. C. O. Fonseca, M. L. Lebrão, R. Laurenti. Cad. Saúde Pública 23 (8). DOI: 10.1590/S0102-311X2007000800019

R packages

BayesMortalityPlus

https://cran.r-project.org/web/packages/BayesMortalityPlus/index.html

Prizes

• 1o. Prêmio Susepe de Pesquisa em seguros (2022) - "Bayes Mortality: A package in R for Bayesian Graduation of Mortality Rates" - V. Lobo, T. Fonseca, M. Alves, L. Silva, L. Figueiredo. (Second place)

• Decision Analysis Practice Award (2022) sponsored by Decision Analysis Society and Society of Decision Professionals Award - Safeguarding the Nation’s Digital Memory: Towards a Bayesian Model of Digital Preservation Risk. M J Barons, S Bhatia, T C O Fonseca, A Green, S Krol, H Merwood, A Mulinder, S Ranade, J Q Smith, T Thornhill, D H Underdown

Reports

On the macroeconomic effects of anticipated and unanticipated fiscal shocks: Evidence from Brazil. L. Vereda Oliveira, and M. Cavalcanti, and V. S. Cerqueira, andT. C. O. Fonseca. Discussion paper 272 (2023), IPEA.

Working Papers

• Dynamic Clustering of Multivariate Time Series: Modeling Time-Varying Memberships. V. S. Sartório and T.C.O. Fonseca. Submitted Arxiv

• Flexible multivariate spatial model with temporal evolution of cross-covariances. With Mariane Branco and Rafael Erbisti.

• Multivariate spatio-temporal models with dynamical varying dependence. with Lucas Moura (DME, UFRJ)

• On the macroeconomic effects of anticipated and unanticipated fiscal shocks: Evidence from Brazil. L. Vereda Oliveira, and M. Cavalcanti, and V. S. Cerqueira, andT. C. O. Fonseca.

• The effects of caesarean sections in private hospitals in Brazil. M. C. Leal, R. M. S. M. Domingues, T. C. O. Fonseca, T. H. Leite, A. P. E. Pereira, J. A. Torres.

• Dynamical Discrete Bayesian Networks. T.C.O.Fonseca with L. E. S. Gomes

• A dynamical model for a group of populations to predict the future sex gap of mortality in Brazil. G.X.Rezende, T.C.O.Fonseca and A.C.S.Bertho.