Luis Raul Pericchi

Dirección Department of Mathematics, University of Puerto Rico
Box 70377 San Juan, PR 00936-8377
Oficina NCN II C-121/ NCN A-206
Horas
Programa Actual
Teléfono (787) 764-0000 88282/ 88283
E-Mail moc.liamg@rpraul, ude.rpu@ihccirep.siul

Educación

PhD, University of London, Imperial College,, 1981

Investigación

Estadística Matemática, Aplicaciones de la Estadí­stica Bayesiana, Estadí­stica Computacional

Publicaciones Representativas

  1. Li, A.; Pericchi, L.; Wang, K. Objective Bayesian Inference in Probit Models with Intrinsic Priors Using Variational Approximations. Entropy 2020, 22, 513.
  2. Arturo J. Fernandez, Cristian D. Correa-Alvarez, Luis R. Pericchi. "Balancing producer and consumer risks in optimal attribute testing: A unified Bayesian/Frequentist design". European Journal of Operational Research.$DOI: https://doi.org/10.1016/j.ejor.2020.03.001$.
  3. Shiru Lin, Yekun Wang, Yinghe Zhao, Luis R. Pericchi, Arturo J. Hernández-Maldonado and Zhongfang Chen. (2020) "Machine-learning-assisted screening of pure-silica zeolites for effective removal of linear siloxanes and derivatives", Journal of Materials Chemistry A, J. Mater. Chem. A, 2020, Advance Article, $https://doi.org/10.1039/C9TA11909D$.
  4. D. Fouskakis, J. K. Innocent and L. Pericchi (2020) Power-expected-posterior prior Bayes factor consistency for nested linear models with increasing dimensions, Statistical Theory and Related Fields, $DOI: 10.1080/24754269.2020.1719355$
  5. Pericchi L. (2020) Discussion on the meeting on‘Signs and sizes:understanding and replicating statistical findings’ J. R. Statist. Soc. A 183, Part 2, pp. 449–469
  6. Williams D.R. , Rast P., L.R. Pericchi and Mulder J. (2019) “Comparing Gaussian Graphical Models with the Posterior Predictive Distribution and Bayesian Model Selection”, Psychological Methods
  7. Bayarri M.J., Berger J.O., Jangc W., Rayd S., Pericchi L.R. and Visser I. (2019) Prior-based Bayesian Information Criterion (PBIC). {f Statistical Theory and Related Fields} (with discussion).Vol. 3, 1, p. 2-13 .$www.tandfonline.com/doi/full/10.1080/24754269.2019.1582126$
  8. Pericchi L.R. and Torres D. (2012) ”Quick anomaly detection by the Newcomb-Benford Law, with applications to electoral processes data from the USA, Puerto Rico and Venezuela” Statistical Science, 26,4, p. 502-516.
  9. Fuquene J.A., Cook J.D. and Pericchi L.R. (2009) "A Case for Robust Bayesian Priors with Applications to Clinical Trials", BAYESIAN ANALYSIS, Vol. 4, Number 4, pp. 817-846. Available electronically in: http://ba.stat.cmu.edu/vol04is04.
  10. Berger J.O. and Pericchi L.R.,  The Intrinsic Bayes Factor for Model Selection and Prediction.  Journal of the American Statistical Association, 91, 433 (1996), 109-122.
  11. Mendez B. and Pericchi L.R. (2009) Assessing Conditional Extremal Risk of Flooding in Puerto Rico. Stochastic Environmental Research and Risk Assessesment, 23, 3, pp.399-410.
  12. Berger J.O. and Pericchi L.R.  Training samples in objective Bayesian model selection.  The Annals of Statistics, Vol. 32, No. 3 (2004), 841-869.
  13. Pericchi, L.R.,   Model Selection and Hypothesis Testing based on Objective Probabilities and Bayes Factors.  Handbook of Statistics, D. Dey and C.R. Rao editors, Vol. 25 (2005), 115-149.

Premios y Becas

  1. Elected Ordinary Member of the International Statistical Institute, 1989
  2. Guggenheim Fellowship (Jul.1997-Jun.1998)
  3. Principal Invesigator, 2006-2008 NSF Grant: "A Synthesis of Objective Bayes Factors for Model Selection and Hypothesis Testing". Amount: $75,000.
  4. Principal Invesigator, 2006-2011 NSF Grant: "Accelerating Puerto Rican students into the National Research Effort in Mathematics and Computer Science". Amount: $500,000.

Additional Information

El Profesor Pericchi ha sido electo Miembro de la International Society for Bayesian Analysis ISBA.
Centro de Bioestadistica y Bioinformatica: