Carlos Daniel M. Paulino

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Departamento de Matemática Instituto Superior Técnico Av. Rovisco Pais, 1, 1049-001 Lisboa PORTUGAL E-mail

REVSTAT editorial: In Memoriam...

Last position:

• Associate Professor in Statistics of the Department of Mathematics of the Instituto Superior Técnico (IST) - Retired (2014).
• Senior Researcher of Center of Statistics and its Applications (CEAUL), Universidade de Lisboa (2014-2023).
• Former President of the Portuguese Statistical Society (SPE) (2012-2014).

Academic degrees/titles:

• Habilitation in Statistics and Operational Research, Faculty of Sciences of the University of Lisbon, 2005.
• Ph.D in Statistics, Institute of Mathematics and Statistics of the University of São Paulo, 1989.
• MSc. in Statistics and Operational Research, Faculty of Sciences of the University of Lisbon, 1984.
• BSc in Chemical Engineering, IST, 1975.

Selected publications:

• Costa, E.G., Paulino, C.D. and Singer, J.M. (2023). Optimal sample size for estimating the mean concentration of invasive organisms in ballast water via a semiparametric Bayesian analysis. Statistical Methods & Applications, 32, 57–74. DOI: 10.1007/s10260-022-00639-0 (here).

• Castro, T.P., Paulino, C.D. and Singer, J.M. (2022). A fair comparison of credible and confidence intervals: an example with binomial proportions. Metron, 80, 371-382. DOI: 10.1007/s40300-021-00225-6.

• Costa, E.G., Paulino, C.D. and Singer, J.M. (2021). Verifying compliance with ballast water standards: a decision-theoretic approach. SORT, 45 (1), 19-32. DOI: 10.2436/20.8080.02.107.

• Costa, E.G., Paulino, C.D. and Singer, J.M. (2021). Sample size for estimating organism concentration in ballast water: A Bayesian approach. Brazilian Journal of Probability and Statistics, 35 (1), 158-171. DOI http://dx.doi.org/10.1214/20-BJPS470.

• Paulino, C.D. and Silva, G.L. (2019). Bayesian comparison of diagnostic tests with largely non-informative missing data. Journal of Statistical Computation and Simulation, 89, 1877-1886. DOI 10.1080/00949655.2019.1601726.

• Amaral Turkman, M.A., Paulino, C.D. and Müller, P. (2019). Computational Bayesian Statistics -- An Introduction. Cambridge University Press, Cambridge (243p).

• Paulino, C.D., Amaral Turkman, M.A., Murteira, B. e Silva, G.L. (2018). Estatística Bayesiana - 2ª edição. Fundação Calouste Gulbenkian, Lisboa (601p).

• Sepúlveda, N., Paulino, C.D. and Drakeley, C. (2015). Sample size and power calculations for detecting changes in malaria transmission using antibody seroconversion rate. Malaria Journal, 14, 529 (14 pp).

• Amaral Turkman, M.A. and Paulino, C.D. (2015). Estatística Bayesiana Computacional - uma introdução. Edições SPE, Lisboa.

• Poleto, F., Paulino, C.D., Singer, J.M. and Molenberghs, G. (2015). Semi-parametric Bayesian analysis of binary responses with a continuous covariate subject to non-random missingness. Statistical Modeling, 15, 1-23.

• Guindani, M., Sepúlveda, N., Paulino, C.D. and Müller, P. (2014). A Bayesian semi-parametric approach for the differential analysis of sequence counts data. Journal of the Royal Statistical Society C, 63, 3, 385-404.

• Poleto, F., Singer, J.M. and Paulino, C.D. (2014). A product-multinomial framework for categorical data analysis with missing responses. Brazilian Journal of Probability and Statistics, 28, 1, 109-139.

• Correia, C., Sepúlveda, N. and Paulino, C.D., Bayesian Genetic Mapping of Binary Trait Loci (2013). In Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and other Statistical Applications; Lita da Silva, J.; Caeiro, F.; Natário, I.; Braumann, C.A. (Eds.), Springer (Studies in Theoretical and Applied Statistics - Selected Papers of the Statistical Societies).

• Paulino, C.D., Silva, G.L. and Branco, M. (2013). A fully Bayesian parametric approach for cytogenetic dosimetry. Brazilian Journal of Probability and Statistics, 27, 1, 70-83.

• Poleto, F., Paulino, C.D., Molenberghs, G. and Singer, J.M. (2011). Inferential implications of over-parameterization: a case study in incomplete categorical data. International Statistical Review, 79, 1, 92-113.

• Poleto, F., Molenberghs, G., Paulino, C.D. and Singer, J.M. (2011). Sensitivity analysis for incomplete continuous data. Test, 20, 3, 589-601.

• Poleto, F., Singer, J.M. and Paulino, C.D. (2011). Comparing diagnostic tests with missing data. J. Applied Statistics, 38, 6, 1207-1222.

• Poleto, F., Singer, J.M. and Paulino, C.D. (2011). Missing data mechanisms and their implications on the analysis of categorical data. Statistics and Computing, 21, 31-43.

• Silva, L., Amaral Turkman, A. and Paulino, C.D. (2010). Statistical evaluation of repeated peak area measurements using Bayesian inference. Applied Radiation and Isotopes, 68, 1397-1402.

• Sepúlveda, N., Paulino, C.D. and Carneiro, J. (2010). Estimation of T-cell repertoire diversity and clonal size distribution by Poisson abundance models. Journal of Immunological Methods, 353, 124-137.

• Achcar, J., Rodrigues, E., Paulino, C.D. and Soares, P. (2010). Non-homogeneous Poisson models with a change-point: an application to ozone peaks in Mexico City. Environmental and Ecological Statistics, 21, 31-43.

• Sepúlveda, N., Paulino, C.D. and Penha-Gonçalves, C. (2009). Bayesian analysis of allelic penetrance models for complex binary traits. Computational Statistics and Data Analysis, 53, 1271-1283.

• Machado, C., Paulino, C.D. and Nunes, F. (2009). Deprivation analysis based on Bayesian latent class models. J. Applied Statistics, 36/8, 871-891.

• Achcar, J.A., Martinez, E.Z., Ruffino-Netto, A., Paulino, C.D. and Soares, P. (2008). A statistical model investigating the prevalence of tuberculosis in New York City using counting processes with two change-points. Epidemiology and Infection, 136, 1599-1605.

• Poleto, F., Singer, J.M. and Paulino, C.D. (2007). A product-multinomial framework for analysis of categorical data with missing responses. In Proceedings of the 22nd International Workshop on Statistical Modelling (J. Castillo, A. Espinal and P. Puig, eds.), p. 508-511, Barcelona.

• Sepúlveda, N., Paulino, C.D., Carneiro, J. and Penha-Gonçalves, C. (2007). Two-gene Interaction Models for Complex Binary Traits Based on the Allelic Penetrance Approach. Heredity, 99, 173-184.

• Paulino, C.D. and Singer, J.M. (2006). Análise de Dados Categorizados. Edgard Blucher, São Paulo.

• Sepúlveda, N., Paulino, C.D. and Penha-Gonçalves, C. (2006). Bayesian Two-gene Interaction Models in Complex Binary Traits. In Statistics in Genomics and Proteomics (W. Urfer and M.A. Turkman, eds.), 27, 103-116, CIM, Coimbra.

• Paulino, C.D., Silva, G.L. and Achcar, J. (2005). Bayesian analysis of correlated misclassified binary data. Computational Statistics and Data Analysis, 49, 1120-1131.

• Paulino, C.D. e Branco, J. (2005). Exercícios de Probabilidade e Estatística. Escolar Editora, Lisboa.

• Paulino, C.D., Amaral Turkman, A. e Murteira, B. (2003). Estatística Bayesiana. Fundação Calouste Gulbenkian, Lisboa.

• Paulino, C.D., Soares, P. and Neuhaus, J. (2003). Binomial Regression with Misclassification. Biometrics, 59, 670-675.
  Notice: This is an electronic version of an article published in Biometrics: complete citation information for the final version of the paper, as published in the print edition of Biometrics, is available on the Blackwell Synergy online delivery service, accessible via the journal's website at http://www.blackwellpublishing.com/journals/BIOM or http://www.blackwell-synergy.com.

• Paulino, C.D. and Soares, P. (2003). Analysis of rates in incomplete Poisson Data. The Statistician, 52, Part 1, 1 - 13.

• Soares, P. and Paulino, C.D. (2001). Incomplete categorical data analysis: A Bayesian perspective. Journal of Statistical Computation and Simulation, 69, 157-170.

• Paulino, C.D. (2000). Analysis of Missing Categorical Data. Revista de Estatística (Statistical Review), 1, 25-46.

• Paulino, C.D., Pacheco, A., Pires, A. e Ferreira da Cunha, Eds. (1999). Afirmar a Estatística: Um desafio para o século XXI. Edições SPE, Lisboa.

• Paulino, C.D. and Silva, G.L. (1999). On the maximum-likelihood analysis of the general linear model in categorical data. Computational Statistics and Data Analysis, 30, 197-204. (ps.zip).

• Paulino, C.D. and Pereira, C.A.B. (1995). Bayesian Methods for Categorical Data under Informative General Censoring. Biometrika, 82(2), 439-446.

• Paulino, C.D. and Pereira, C.A.B. (1994). On Identifiability of Parametric Statistical Models. Journal of the Italian Statistical Society, 3(1), 125-151.

• Paulino, C.D. (1993). A Teoria Clássica da Suficiência numa Caracterização Bayesiana de Identificabilidade. 1° Congresso Ibero-Americano de Estatística e Investigação Operacional, Cáceres, Outubro 1992. Artigo do livro Estatística Robusta, Extremos e mais alguns temas. Col. Novas Tecnologias/Estatística, Salamandra, Lisboa.

• Paulino, C.D. (1993). I. O modelo estatístico bayesiano e sua estrutura matemática; II. Independência condicional e suficiência bayesiana amostral; III. Identificabilidade paramétrica. Capítulos do livro Teoria Estatística, pp. 118-176, ed. Carlos Pereira, 19° Colóquio Brasileiro de Matemática, IMPA, Rio de Janeiro.

• Paulino, C.D. and Pereira, C.A.B. (1992). Bayesian Analysis of Categorical Data Informatively Censored. Communications in Statistics - Theory Meth, 21(9), 2689-2705.

• Paulino, C.D. (1991). Analysis of Incomplete Categorical Data: a Survey of the Conditional Maximum Likelihood and Weighted Least Squares Approaches. Brazilian Journal of Probability and Statistics (REBRAPE), 5, 1-42.

Research:

Main areas of interest:

• Statistical Inference
• Bayesian Statistics
• Categorical Data
• Missing Data
• Biostatistics

Teaching:

• Courses for Graduated Students:
  • Statistical Theory (PhD, University of São Paulo)
  • Analysis of Categorical Data (MMAC, IST)
  • Survival Analysis (MMAC, IST)
  • Bayesian Statistics (MMAC, IST and Faculty of Sciences - University of Lisbon)
  • Statistical Inference (MMAC, IST)
  • Regression and Numerical Analysis (MSc., Faculty of Pharmacology - University of Lisbon)
  • Mathematical Statistics (MSc.-Bolonha, IST).
• Courses for Students of Applied Mathematics and Computation (LMAC, IST):
  • Categorical Data Analysis
  • Statistical Inference and Decision - I
  • Statistical Inference and Decision - II
  • Multivariate Models
  • Statistical Inference
  • Statistics~
• Courses for Engineering Students:
  • Probability and Statistics
    • Combinatorial Analysis Notes (in Portuguese)
  • Statistical Methods
  • Linear Algebra
• Other courses:
  • Introduction to Bayesian Statistics: Fundamentals, Methods and Applications. (Short course, Faculty of Sciences of the University of Porto, Porto, Portugal - 2020)
  • Analysis of complete and incomplete categorical data via Catdata (library of functions in R). (Short course, ESALQ/University of São Paulo and Federal University of Ceará, São Paulo and Fortaleza, Brazil - 2007)
  • Bayesian Statistics. (Short course, Federal University of Rio Grande do Norte, Natal, Brazil - 2007)
  • Special Topics of Statistics - Multivariate Analysis (BSc. in Statistics, University of São Paulo, Brazil - 1988)
  • Probability and Statistics (Training - Renault, Lisbon - Portugal)

• Last update: 18/04/2023