Carlos Daniel M. Paulino

Se voce deseja a versão em Português pressione aqui.

Current position:

• Associate Professor in Statistics of the Department of Mathematics of the Instituto Superior Técnico (IST) - since 1995.

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:

• SILVA, L., AMARAL TURKMAN, A. and PAULINO, C.D. (2009). Statistical evaluation of repeated peak area measurements using Bayesian inference. Applied Radiation and Isotopes (DOI: 10.1016/j.apradiso.2010.01.039).

• SEPÚLVEDA, N., PAULINO, C.D. and CARNEIRO, J. (2009). Estimation of T-cell repertoire diversity and clonal size distribution by Poisson abundance models. Journal of Immunological Methods (DOI:10.1016/j.jim.2009.11.009).

• ACHCAR, J., RODRIGUES, E., PAULINO, C.D. and SOARES, P. (2009). Non-homogeneous Poisson models with a change-point: an application to ozone peaks in Mexico City. Environmental and Ecological Statistics (DOI: 10.1007/s10651-009-0114-3).

• POLETO, F., SINGER, J. and PAULINO, C. D. (2009). Missing data mechanisms and their implications on the analysis of categorical data. Statistics and Computing (DOI: 10.1007/s11222-009-9143-x).

• 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. 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. e SINGER, J. M. (2006). Análise de Dados Categorizados. Edgard Blucher, São Paulo.(in Portuguese)

• 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, p. 103 - 116, CIM, Coimbra.

• PAULINO, C. D., SILVA, G. 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. (in Portuguese)

• PAULINO, C. D., AMARAL TURKMAN, A. e MURTEIRA, B. (2003). Estatística Bayesiana. Fundação Calouste Gulbenkian, Lisboa. (in Portuguese)

• 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), Vol.1, 25 - 46 (in portuguese).

• PAULINO, C. D., PACHECO, A., PIRES, A. e FERREIRA DA CUNHA, eds. (1999). Afirmar a Estatística: Um desafio para o século XXI. (Edited book) Edições SPE, Lisboa. (in portuguese)

• PAULINO, C.D.M. 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.M. AND PEREIRA, C.A.B. (1995). Bayesian Methods for Categorical Data under Informative General Censoring. Biometrika 82(2), 439-446.

• PAULINO, C.D.M. AND PEREIRA, C.A.B. (1994). On Identifiability of Parametric Statistical Models. Journal of the Italian Statistical Society (Statistical Methods and Applications) , 3(1), 125-151.

• PAULINO, C.D.M. (1993). Classical Theory of Sufficiency on a Bayesian Characterization of Identifiability. 1° Congresso Ibero-Americano de Estatística e Investigação Operacional, Cáceres, Outubro 1992. Article (in portuguese) in the book Estatística Robusta, Extremos e mais alguns temas . Col. Novas Tecnologias/Estatística, Salamandra, Lisboa. (in portuguese)

• PAULINO, C.D.M. (1993). I. Bayesian statistical model and its mathematical structure; II. Conditional Independence and sampling Bayesian suficiency; III. Parametric Identifiability. Chapters (in portuguese) of the book Teoria Estatística, pp. 118-176, ed. Carlos Pereira, 19° Colóquio Brasileiro de Matemática, IMPA, Rio de Janeiro. (in portuguese)

• PAULINO, C.D.M. e PEREIRA, C.A.B. (1992). Bayesian Analysis of Categorical Data Informatively Censored. Communications in Statistics - Theory Meth., 21(9), 2689-2705.

• PAULINO, C.D.M. (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), vol. 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 (MSc., IST)
  • Survival Analysis (MSc., IST)
  • Bayesian Statistics (MSc., IST and Faculty of Sciences - University of Lisbon)
  • Statistical Inference (MSc., IST)
  • Regression and Numerical Analysis (MSc., Faculty of Pharmacology - University of Lisbon).
• Courses for Students of Applied Mathematics and Computation (LMAC, IST):
  • Categorical Data Analysis
  • Statistical Inference and Decision - I
  • Statistical Inference and Decision - II
  • Mathematical Statistics
  • Multivariate Models
  • Statistical Inference
  • Statistics
• Courses for Engineering Students:
  • Probability and Statistics
  • Statistical Methods
  • Linear Algebra
• Other courses:
  • Introduction to Bayesian Statistics via WinBUGS (Minicurso, FCUL - CEAUL, Lisboa - 17-18/12/2009)
  • Analysis of Missing Categorical Data (Minicurso, FCUL - CEAUL, Lisboa - 22-23/01/2009)
  • Analysis of complete and incomplete categorical data via Catdata (library of functions in R) (Minicurso, ESALQ/Universidade de São Paulo e Universidade Federal do Ceará, Fortaleza, Brasil - 2007; CEAUL, Lisboa - 2009)
  • Estatística Bayesiana. (Minicurso, Universidade Federal do Rio Grande do Norte, Natal, Brasil - 2007)
  • Special Topics of Statistics - Multivariate Analysis (BSc., Univ. São Paulo - 1988)
  • Probability and Statistics (Training, Renault)

• Last update: 31/12/2009