Recent Technical Reports
Luis R. Pericchi, Maria-Eglee Perez. 2017. Converting P-Values in Adaptive Robust Lower Bounds of Posterior Probabilities to increase the reproducible Scientific "Findings", https://arxiv.org/abs/1711.06219
Publications:
128. Pericchi G., Luis R. (2025) Discussion of ``Model Uncertainty and Missing Data: An Objective Bayesian Perspective'', by G. Garcia-Donato, M.E. Castellanos, E. Cabras, A. Quiros and A. Forte. BAYESIAN ANALYSIS. (In press).
127. Santos, Angélica Rosario, Luis Pericchi Guerra, and Hernando Mattei. (2024)"A Bayesian Projection of the Total
Fertility Rate of Puerto Rico: 2020-2050." arXiv preprint arXiv:2308.14168 (2023). Puerto Rico Health Sciences Journal. [P R Health Sci J 2024;43(3):125-131]
126. Almodóvar-Rivera, I.A; Pericchi-Guerra, L.R. (2024) An Objective and Robust Bayes Factor for the Hypothesis Test One Sample and Two
Population Means. Entropy 2024, 26, 88. https://doi.org/10.3390/ e26010088.
125. Cruz G, Ramos-Cartagena JM, Torres-Russe JL, Colón-López V, Ortiz-Ortiz KJ, Pericchi L, Deshmukh AA, Ortiz AP.(2023) Barriers and facilitators to anal cancer screening among people living with HIV in Puerto Rico. BMC Public Health. 2023 Oct 6;23(1):1940. doi: 10.1186/s12889-023-16847-6. PMID: 37803344; PMCID: PMC10559598.
124. Shen N., Gonzalez B. and Pericchi L. (2023) "Comparison Between Bayesian and Frequentist Tail Probabilities Estimates", The New England Journal of Statistics and Data Science. Volume 1, Issue 2 (2023), pp. 208–215. $https://doi.org/10.51387/23-NEJSDS39$
123. Pericchi, L. (2023) "Invited Discussion of J.O. Berger: Four Types of Frequentism and Their Interplay with Bayesianism", The New England Journal of Statistics and Data Science. DOI:$https://doi.org/10.51387/23-NEJSDS4B$
122. Vélez Ramos D, Pericchi Guerra LR, Pérez Hernández ME. "From p-Values to Posterior Probabilities of Null Hypotheses". Entropy. 2023; 25(4):618. https://doi.org/10.3390/e25040618
121. Soto-Salgado M, Suárez E, Viera-Rojas T, Pericchi L, Ramos-Cartagena J, Deshmukh A,Tirado-Gómez M
and Ana Patricia Ortiz A. (2022) "Development of a multivariable prediction model for anal high-grade squamous intraepithelial lesions in persons living
with HIV in Puerto Rico: A cross-sectional study". The Lancet RegionalHealth-Americas, 2022, 100382. $https://doi.org/10.1016/j.lana.2022.100382$
120. Correa-Álvarez, C.D., Salazar-Uribe, J.C. and Pericchi-Guerra, L.R. Bayesian multilevel logistic regression models: a case study applied to the results of two questionnaires administered to university students. Comput Stat (2022). https://doi.org/10.1007/s00180-022-01287-4.
119. Berger JO, Garcia-Donato G, Moreno E, and Pericchi LR (2022) "Objective Bayesian Testing and Model Uncertainty". Handbook of Bayesian,
Fiducial, and Frequentist Inference. CRC Press, p.132-160.
118. Velez D., Perez M.E. and Pericchi L.R. (2022) Increasing the Replicability for Linear Models via Adaptive Significance Levels". TEST, Feb. 2022. https://doi.org/10.1007/s11749-022-00803-4.
117. Li, A.; Pericchi, L.; Wang, K. (2020) Objective Bayesian Inference in Probit Models with Intrinsic Priors Using Variational Approximations. Entropy 2020, 22, 513.
116. Arturo J. Fernandez, Cristian D. Correa-Alvarez, Luis R. Pericchi. (2020) "Balancing producer and consumer risks in optimal attribute testing: A
unified Bayesian/Frequentist design". European Journal of Operational Research.
Volume 286, Issue 2, 16 October 2020, Pages 576-587.
DOI: https://doi.org/10.1016/j.ejor.2020.03.001.
115. 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.
114. 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
113. Pericchi L. (2020) Discussion on the meeting on‘Signs and sizes:understand-
ing and replicating statistical findings’ J. R. Statist. Soc. A
183, Part 2, pp. 449–469
112. Williams, D. R., Rast, P., Pericchi, L. R., and Mulder, J. (2020). Comparing Gaussian
Graphical Models With the Posterior Predictive Distribution and Bayesian Model Selection.
Psychological Methods, 25(5), 653–672. https://doi.org/10.1037/met0000254
111. Bayarri M.J., Berger J.O., Jangc W., Rayd S., Pericchi L.R. and Visser I. (2019) Prior-based Bayesian Information Criterion (PBIC). Statistical Theory and Related Fields (with discussion).Vol. 3, 1, p. 2-13. https://www.tandfonline.com/doi/abs/10.1080/24754269.2019.1582126?journalCode=tstf20
110. Pericchi, L. Contributed Discussion of: Using Stacking to Average Bayesian Predictive Distributions by Yuling Yao, Aki Vehtari, Daniel Simpson, and Andrew Gelman Bayesian Analysis (2018) 13, Number 3, pp. 988-989.
109. Cruz, J. & Pericchi, L. (2018). Sequential Bayesian tests and the independence hypothesis or naive Bayes. Rev. Fac. Cienc., Univ. Nacional de Colombia,Medellin, 7(1), 112-123. DOI: https://doi.org/10.15446/rev.fac.cienc.v7n1.67107
108. Mulder J. and Pericchi L.R. (2017) "The matrix-F prior for estimating and testing covariance matrices", Bayesian Analysis. Volume 13, Number 4 (2018), 1189-1210.
107. Jimenez R, Klimek P, Pericchi L* and Thurner S, (2017) "Fraud Detection, Electoral". Wiley Stat Reference: Statistics References Online. First published: 14 August 2018 https : ==doi:org=10:1002=9781118445112:stat08006:
106. Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E. J., Berk, R., Bollen, K. A., Brembs, B., Brown, L., Camerer, C., Cesarini, D., Chambers, C. D., Clyde, M., Cook, T. D., De Boeck, P., Dienes, Z., Dreber, A., Easwaran, K., E_erson, C., Fehr, E., Fidler, F., Field, A. P., Forster, M., George, E. I., Gonzalez, R., Goodman, S., Green, E., Green, D. P., Greenwald, A., Had_eld, J. D., Hedges, L. V., Held, L., Ho, T.{H., Hoijtink, H., Jones, J. H., Hruschka, D. J., Imai, K., Imbens, G., Ioannidis, J. P. A., Jeon, M., Kirchler, M., Laibson, D., List, J., Little, R., Lupia, A., Machery, E., Maxwell, S. E., McCarthy, M., Moore, D., Morgan, S. L., Munaf, M., Nakagawa, S., Nyhan, B., Parker, T. H., Pericchi, L., Perugini, M., Rouder, J., Rousseau, J., Savalei, V., Schnbrodt, F. D., Sellke, T., Sinclair, B., Tingley, D., Van Zandt, T., Vazire, S., Watts, D. J., Winship, C., Wolpert, R. L., Xie, Y., Young, C., Zinman, J., Johnson, V. E. Redefine Statistical Signignificance. Nature Human Behavior, published September 01, 2017Volume 2, Issue 1, Pages 6 .
105. Perez M.E., Pericchi L.R. and Ramirez I. (2017) "The Scaled Beta2 Distribution as a Robust Prior for Scales". Bayesian Analysis, Volume 12, Number 3 (September), 615-637.
104. Torres D, Mattei H, Pericchi L.R, Zevallos J.C (2017) Comparative Longterm Mortality Trends in Cancer vs. Ischemic Heart Disease in Puerto Rico. Puerto Rico Health Sciences Journal, Vol. 36 No. 2 June, pp. 55-60.
103. Pericchi L.R., Duconge J., J.R. Miranda-Massari, Gonzalez M.J., Nieves M., Torres D. and Hickey, S. (2017) Simulation-Based Design of Phase I Clinical Trial of Intravenous Vitamin C Treatment. International Journal of Cancer Research and Therapy, Vol. I, Issue I, p.1-4
102. Ramirez-Hassan A. and Pericchi L. (2018) "Effects of prior distributions: An application to piped water demand", Brazilian Journal of Probability and Statistics, Volume 32, Number 1 , 1-19.
101. J. F. Ruiz-Calderon, H. Cavallin, S. J. Song, A. Novoselac, L. R. Pericchi, J. N. Hernandez, R. Rios, O. H. Branch, H. Pereira, L. C. Paulino, M. J. Blaser, R. Knight, M. G. Dominguez-Bello. (2016) Walls talk: Microbial biogeography of homes spanning urbanization. Sci. Adv. 2, e1501061.
100. Li A. and Pericchi L.R. (2016) Model Selection. Wiley StatsRef: Statistics Reference Online. Wiley Online Library. https://doi.org/10.1002/9781118445112.stat06424.pub2
99. Pericchi L.R. and Pereira CAB (2016) Adaptative significance levels using optimal decision rules: Balancing by weighting the error probabilities. Brazilian Journal of Probability and Statistics , Vol. 30, No. 1, 70-90 DOI: 10.1214/14-BJPS257.
98. Merida F, Chiu-Lam A, Bohorquez A, Maldonado-Camargo L, Perez ME, Pericchi L, Torres-Lugo M, Rinaldi C. (2015) Optimization of synthesis and peptization steps to obtain iron oxide nanoparticles with high energy dissipation rates. Journal of Magnetism and Magnetic Materials 394, 361-371.
97. Fuquene J, Alvarez M and Pericchi LR (2015) A robust Bayesian dynamic linear model for Latin-American economic time series: the Mexico and Puerto Rico cases. Latin American Economic Review, 24:6.
96. Berger J.O. and Pericchi L.R. (2015) Bayes Factors. Wiley StatsRef: Statistics Reference Online. Wiley Online Library. 1-14.
95. Zevallos J.C, Santiago F, Gonz_alez J, Rodriguez A, Pericchi L, Rodriguez-Mercado R and Nobo U. (2015) Burden of Stroke in Puerto Rico. International Journal of Stroke, Volume 10, Issue 1, pages 117-119.
94. Discussion of "Robust Bayesian Graphical Modeling Using Dirichlet t-Distributions" by Finegold and Drton (2014), Bayesian Analysis, 9, 3, p. 586 .
93. Moreno E. and Pericchi L.R. (2014) Intrinsic Priors for Objective Bayesian Model Selection. Advances in Econometrics, in Ivan Jeliazkov, Dale J. Poirier (ed.) Bayesian Model Comparison (Advances in Econometrics, Volume 34) Emerald Group Pub.
92. Pericchi L.R. Pereira C.A.B and Perez M.E. (2014) "Adaptive revised standards for statistical evidence", Letter to the Editor, PNAS (Proceedings of the National Academy of Sciences), Vol. 111, No. 19,http : ==www:pnas:org=cgi=doi=10:1073=pnas:1322191111
(Online only), PMC4024868.blishing Limited, pp.279 - 300.
91. Perez M.E. and Pericchi L.R (2014) Changing Statistical Significance with the Amount of Information: The adaptive significance level. Statistics and Probability Letters, 85, pp.20-24. http : ==www:sciencedirect:com=science=article=pii=S0167715213003611
90. Fuquene, J., Perez, M.E. and Pericchi, L.R. (2014) "An alternative to the Inverted Gamma for the variances to modelling outliers and structural breaks in dynamic models". Brazilian Journal of Probability and Statistics, Volume 28, Number 2, pp. 288-299.
89. Maldonado-Contreras A, Shrinivasrao MP, Xue-Song Z, Pericchi L, Alarcon T, Contreras M, Linz B, Blaser MJ and Dominguez-Bello M. (2013) Phylogeographic evidence of cognate recognition site patterns and transformation efficiency differences in H. pylori: theory of strain dominance. BioMed Central BMC Microbiology, Volume13, Issue 1, P. 211.
88. Berger, J.O., Bayarri M.J. and Pericchi, L.R. (2013) The Effective Sample Size. Econometrics Review, 33,p.197-217.
87. Almodovar I., Pericchi L. (2012) New Criteria for the Choice of Training Sample Size for Model Selection and Prediction: The Cubic Root Rule. Revista Facultad de Ciencias Universidad Nacional de Colombia, Sede Medellin. Vol 1 N 1, p. 7-22. ISSN 0121-747X (Invited paper).
86. Zevallos JC, Banchs HL, Altieri PI, Pericchi LR, Gonzalez JA, Carcia-Palieri MR, Jimenez L, OSterman A, Gonzalez M, Yarzebski J and Goldberg RJ. (2012) "Epidemiology of Heart Failure in Puerto RIcans: The Puerto Rico Heart Failure Study". Editorial Comment by Rodriguez-Ospina, LF El Bisturi, Diciembre 2012, pp. 4-11.
85. Zevallos JC, Yarzebski J, Banchs H, Gonzalez-Sanchez JA, Mattei H, Goldberg RJ, Gonzalez M, Quevedo J, Mojica G, Pericchi LR, Garcia-Palmieri MR (2012) Gender Disparities in Puerto Ricans Hospitalized with an Initial Acute Myocardial Infarction: A Population based Perspective. Puerto Rico Health Sciences Journal, Vol. 31, No 4, p. 192-198.
84. Pericchi L.R. and Pereira C.A.B. (2012)"Towards a general theory of optimal testing", AIP Conf. Proc. 1490, pp. 31-35; doi: http://dx.doi.org/10.1063/1.4759586 (5 pages) XI BRAZILIAN MEETING ON BAYESIAN STATISTICS: EBEB 2012 Date: 18-22 March 2012 Location: Amparo-SP, Brazil.
83. O'Hagan A. and Pericchi L.R. (2012) "Bayesian heavy-tailed models and conict resolution: a review".Brazilian Journal of Probability and Statistics, Vol. 26, No. 4, 372-401.
82. Pericchi L.R. and Torres D. (2011) "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.
81. Cook J., Fuquene J. and Pericchi L.R. (2011) "Skeptical and Optimistic Robust Priors for Clinical Trials". Revista Colombiana de Probabilidad y Estadistica, volumen 34, no. 2, pp. 333-345.
80. Pericchi, L.R. (2011) "Marginal Probability: Its Use in Bayesian Statistics as Model Evidence", International Encyclopedia of Statistical Science, Part 13, 765-767, DOI: 10.1007/978-3-642-04898-2-346, http://www.springerlink.com/content/v466886551kt6836.
79. Pericchi, L.R. (2011) Discussion of Polson N.G. and Scott J.G. "Shrink globally, act locally: Sparse Bayesian regularization and prediction." Bayesian Statistics 9, Bernardo JM et al Eds. p. 531-2.
78. Pericchi, L.R. (2011) Invited Discussion of: "Integrated Objective Bayesian Estimation and Hypothesis Testing", by Bernardo, J.M. In Bayesian Statistics 9, Bernardo et al editors. Oxford University Press. p. 25-30.
77. Pericchi, L.R. (2010) "How large should the training sample be?" In the book: "Frontiers of Decision Making and Bayesian Analysis. In Honor of James O. Berger", Chen MH et al editors. Springer, 4.2, p. 130-142.
76. 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.
75. Mendez B. and Pericchi L.R. (2009) Assessing Conditional Extremal Risk of Flooding in Puerto Rico. Stoch. Environ. Res. Risk Assess,23, 3, pp.399-410.
74. Cook J.D. and Pericchi (2008) "Robust Bayesian Priors with applications to Clinical Trials: Information and Cross-Entropic Approaches". In Bayesian Inference and Maximum Entropy Methods in Science and Engineering. De Souza Lauretto et al editors. American Institute of Physics, pp. 278-285.
73. Maria G. Dom__nguez-Bello, Maria E. P_erez, Maria C. Bortolini, Francisco M. Salzano, Luis R. Pericchi, Orlisbeth Zambrano-Guzman, Bodo Linz. (2008) "Amerindian Helicobacter pylori strains go extinct, as European strains expand their host range". Public Library of Science. PLoS ONE 3(10): e3307 doi:10.1371/journal.pone.0003307
72. Pericchi L.R. and Liu G. and Torres D. (2008) "Objective Bayes Factors for Informed Hypothesis: Completing the Informed Hypothesis and Splitting the Bayes Factors". In the book: "Practical Bayesian Approaches to Testing Behavioral and Social Science Hypotheses" Chapter 7. Editors: Herbert Hoijtink Irene Klugkist and Paul A. Boelen. Publisher: Springer,pp. 131-154.
71. Godoy-Vitorino F, Ley RE, Gao Z, Pei Z, Ortiz-Zuazaga H, Pericchi LR, Garcia-Amado MA, Michelangeli F, Blaser MJ, Gordon JI, Dominguez-Bello M.G. (2008) The crop bacterial community of the hoatzin, a neotropical folivorous ying bird. Applied and Environmental Microbiology. 74(19), pp. 5905-5912.
70. Marini E, Maldonado A, Cabras S, Hidalgo G, Bu_a R, Marin A, Flores G, Racugno W, Pericchi LR, Castellanos ME, Groeschl M, Blaser MJ, Dominguez-Bello MG. (2007) Helicobacter pylori and intestinal parasites are not detrimental to the nutritional status of Amerindians. American Journal of Tropical Medicine and Hygiene 76: pp. 534-540.
69. Sisson S.A., Pericchi L.R. and Coles S.G. (2006) A case for a reassessment of the risk of extreme hydrological hazards in the Caribbean". Stoch. Environ. Res. Risk Assess, 20, pp. 296-306.
68. Pericchi L.R. (2005) Model Selection and Hypothesis Testing based on Objective Probabilities and Bayes Factors". Elsevier B.V. Handbook of Statistics, vol. 25. p. 115-149.
67. Berger J.O. and Pericchi LR. (2004) Training samples in objective Bayesian model selection". Annals of Statistics, 32, 3, p. 841-869.
66. Coles S. and Pericchi L.R. (2003) \Anticipating catastrophes through extreme value modeling". Journal of the Royal Statistical Society, Series C: Applied Statistics, 52, 4, p. 405-416.
65. Pericchi, L.R. (2003) Invited discussion of: “Could Fisher, Je_reys and Neyman have agreed on testing?", by J.O. Berger, Statistical Science, Vol. 18, No. 1, pp. 13-15.
64. Coles S., Pericchi L.R. and Sisson S. (2003) A fully probabilistic approach to extreme rainfall modeling". Journal of Hydrology, 273, pp. 35-50.
63. Pericchi L. R. and Coles S. (2003) Pudo haber sido anticipada probabilisticamente la lluvia extrema que causo la tragedia de Vargas?". Acta Cientifica Venezolana, Vol. 54, Suplemento No. 1: 17-21, 2003.
62. Dominguez-Bello M.G. Beker B. Guelrud M. Vivas J. Peraza S. Perez M.E. and Pericchi L.R. (2002) Socioeconomic and Seasonal variations of H. Pylory infection in patients in Venezuela". American Journal of Tropical Medicine and Hygiene, Vol. 66, pp. 49-51.
61. Pericchi L.R. (2002) "Bayes Factors". Encyclopedia of Environmetrics. Editors: El-Shaarawi A. and Piegorsh W. John Wiley and Sons. Vol.1, pp. 148-150.
60. Kadane J., Moreno E., P_erez M.E. and Pericchi L.R. (2002) \Applying Non-Parametric Robust Bayesian Analysis to Non-Opinionated Judicial Neutrality", Journal of Statistical Planning and Inference, 102, p. 425-39.
59. Rodriguez A. and Pericchi L.R. (2001) “Intrinsic Bayes Factors for Dynamic Models". Proceedings of the ISBA2000, VI World Meeting of the International Society for Bayesian Analysis, Crete, Greece, June 2000, E. George and P. Nanopoulus eds., Offcial Publications of the European Communities, Luxembourg, pp.459-468.
58. Berger J.O. and Pericchi L.R. (2001) "Objective Bayesian Model Selection. Introduction and Comparisons", in Lectures Notes of the Institute of Mathematical Statistics. "Model Selection", editor: P. Lahiri, pp. 135-207.
57. Pacheco N., Mago V., Gomez I., Gueneau P., Guelrud., Reyes N., Pericchi L.R. and Dominguez-Bello M.G. (2001) “Comparison of PCR and common clinical tests for the diagnosis of H. pylori in Dyspeptic patients" Diagnostic Microbiology and Infectious Disease, 39, p. 207-10.
56. Perez M.E., Glass R., Alvarez G., Pericchi L.R., Gonzalez R., Kapikian A., and Perez-Schael, I.,(2001) “Rhesus Rotavirus-based quadrivalent vaccine is effcacious despite age, socioeconomic conditions and seasonality in Venezuela", Vaccine, Vol.19, No. 7-8, p. 976-981.
55. Marini E., Sanna E., Paoli G., Pericchi L.R., Taglioli L. and Floris G. (2000) "Digital dermatoglyphic patterns of the Piaroa and genetic relationships among several South American Indian populations", in The State of Dermatoglyphics, Durham, N.M. et al editors Melles Press, New York. p. 3-15.
54. Berger J.O and Pericchi L.R. (1998) " On Criticisms and Comparisons of default Bayes Factors for Model Selection and Hypothesis Testing"(wit discussion). Special Issue of: Rasegna di Metodi Statici ed Applicazioni. p. 1-50.
53. Key J.T., Pericchi L.R. and Smith A.F.M. (1998) “Choosing Among Models When None of them Are True” (with discussion), Special Issue of: Rasegna di Metodi Statici ed Applicazioni. P.333-361.
52. Moreno E., Pericchi L.R. and Kadane J. (1998) " A Robust Bayesian look at the theory of Precise Measurement", in the book: Decision Research from Bayesian Approaches to Normative Systems. Editors: Shantan J. et al. Kluwer Academic Publishers.
51. Berger J.O. Pericchi L.R. and Varshavsky J.A (1998) "Bayes Factors and Marginal Distributions in Invariant Situations". Sankya: The Indian Journal of Statistics. Special Issue on Bayesian Analysis. Vol 60, Series A, part.3 , p.307-321.
50. Berger J.O. and Pericchi L.R. (1998) "Accurate and Stable Bayesian Model Selection: The Median Intrinsic Bayes Factor". Sankya: The Indian Journal of Statistics Special Issue on Bayesian Analysis. Vol.60, Serie B, Part.1, p.1-18.
49. Key J. T., Pericchi L.R.and Smith A.F.M. (1998) "Bayesian Model Choice: What and Why?"(with discussion) Bayesian Statistics 6, invited conference. Bernardo et al editors. Oxford
48. Nadal N. and Pericchi L.R. (1998) "An automatic Bayesian procedure for likelihoods with shifted origin". The Statistician , 47 Part 2, pp. 323-332. University Press, p. 343-370.
47. Dominguez-Bello M.G., Perez M.E. and Pericchi L.R.(et.al) (1997) "Modification of the Christiansen urease test for Detection of Helicobacter Pylori", Diagnostic Microbiology and Infections Disease. Vol. 28, pp. 235-244.
46. Sanso B., Pericchi L.R. and Moreno E. (1996) “On the Robustness of the Intrinsic Bayes Factor for Nested Models”. Lecture Notes of the Institute of Mathematical Statistics, Bayesian Robustness, p. 155-174.
45. Pericchi L.R. (1996) Beyond the effect PPI in the scientific research in Venezuela. INTERCIENCIA. Vol. 21, p.94-97.
44. Berger J.O. and Pericchi L.R. (1996) On the Justification of Default and Intrinsic Bayes Factor. In Modeling and Prediction Honoring S. Geisser, p. 276-293. Editors Lee J.C., Johnson W.O. y Zellner A. Springer Verlag, NY.
43. Berger J.O. and Pericchi L.R. (1996) The Intrinsic Bayes Factor for Linear Models (invited discussant: Prof. D. Dey, University of Connecticut, USA). Bayesian Statistics 5, Bernardo J.M. et al editors. Oxford University Press. Invited conference. p. 25-44.
42. Berger J.O. and Pericchi L.R. (1996) The Intrinsic Bayes Factor for Model Selection and Prediction. Journal of the American Statistical Association, 91, 433, p. 109-122.
41. Pericchi, L.R.(1995) Invited Discussion of "The relation between theory and application in statistics" by Sir David R. Cox, Test, 4, pp. 245-248.
40. Pericchi L.R. and Sanso B. (1995) A note on Bounded Inuence in Bayesian Analysis. Biometrika, 82, 1, p.223-5.
39. Pericchi, L.R. (1994) Invited discussion of "An overview of robust Bayesian analysis" by J.O. Berger. Test 3, pp. 67-69.
38. Pericchi L.R. (1994) El Efecto PPI en Venezuela: 1990-1994. Acta Cientifica Venezolana, 45, p. 264-267.
37. Perez M.E. and Pericchi L.R. (1994) A case study on the Bayesian Analysis of 2x2 tables with two fixed margins. Revista Brasileira de robabilidade e Estatistica REBRAPE , 1, p. 27-37.
36. Sanso B. and Pericchi L.R. (1994) “On Near Ignorance Classes” Revista Brasileira de Probabilidade e Estatistica REBRAPE, 2, p.119-126.
35. Sanso B. and Pericchi L.R. (1994) “Large Classes of Proper Priors for Linear Models”. Communications in Statistics, Theory and Methods. Vol. 23 (9), p. 2493-2501.
34. Pericchi L.R. and Perez M.E. (1994) Bayesian Robustness with more than one Sampling Model (with discussion). Journal of Statistical Planning and Inference, Vol. 40, 2-3, p. 279-294.
33. Pericchi L.R. and Nadal N. (1993) Analysis of Irregular Likelihoods by Grouping the Likelihood and Bayesian Marginalization. Proceedings of the Conference on Statistical Inference and Biostatistics, Sprott D. Editor, p. 201-213.
32. Moreno E. and Pericchi L.R. (1993) Prior Assessment for Bands of Probability measures: Empirical Bayes Analysis. TEST, 2, p.101-110.
31. Moreno E. and Pericchi L.R. (1993) On Epsilon - Contaminated Priors with Quantile and Piece-Wise Unimodality Constraints. Communications in Statistics.
30. Moreno E. and Pericchi L.R. (1993) A Hierarchical Epsilon - Contaminated Model. Journal of Statistical Planning and Inference, 37, p. 159-167.Theory and Methods, 22(7), pp. 1963-1978.
29. Pericchi L.R., Sanso B. and Smith A.F.M. (1993) Posterior Cumulant relationships in Bayesian inference involving the Exponential Family. Journal of the American Statistical Association Vol. 88 , pp. 1419-1426.
28. Campos A. and Pericchi L.R. (1992) Statistical Assessment of Total Heat Losses from Externally Finned Tubes using various Spatially-Weighted Mean Biot Numbers. International Journal of Heat and Fluid Flow. Vol. 13, N 4, p. 399-407.
27. Sanso B. and Pericchi L.R. (1992) Near Ignorance Classes of Log-Concave priors for the Location Model. Test, 1(1), p. 27-32.
26. Pericchi L.R. and Smith A.F.M. (1992) Exact and Approximate Posterior Moments for a Normal Location Parameter. J. Roy. Statist. Soc. Series B (methodological), 54 (3), p. 793 - 804.
25. Moreno E. and Pericchi L.R. (1992) Subjetivismo sin Dogmatismo: Inferencia Bayesiana Robusta. (with discussion). Estadística Española , 34 (129), p. 1-60.
24. Perez M.E. and Pericchi L.R. (1992) Analysis of Multistage Survey as a Bayesian Hierarchical Model. Bayesian Statistics 4, Berger, J., Bernardo, J.M., Dawid, P. and Smith, A.F.M. Editors. Oxford University Press, p. 723 - 730.
23. Moreno E. and Pericchi L.R. (1992) Bands of Probability Measures. A Robust Bayesian Analysis. Bayesian Statistics 4, Berger, J., Bernardo, J.M., Dawid, P. and Smith, A.F.M. Editors. Oxford University Press, p. 707 - 713.
22. Moreno E. and Pericchi L.R. (1992) Analisis empirico Bayes en bandas de medidas de probabilidad. Actas IV Congreso Latinoamericano de Prob. y Estad. Mat., Publicaciones de la Soc. Bernoulli Latinoamericana , p. 154-171.
21. Sanso B.and Pericchi L.R. (1992) Imprecise Bayesian Inference for Location Models. Actas IV Congreso Latinoamericano de Prob. y Estad. Mat., Publicaciones de la Soc. Bernoulli Latinoamericana , p. 221-227.
20. Perez M.E. and Pericchi L.R. (1992) A Bayesian Approach to Analysis of Multistage Survey. Actas IV Congreso Latinoamericano de Prob. y Estad. Mat., Publicaciones de la Soc. Bernoulli Latinoamericana , p. 189-207.
19. Moreno E. and Pericchi L.R. (1991) Robust Bayesian analysis for epsilon-contaminations with shape and quantile constraints. Proc. Fifth Intern. Symp. App. Stoch. Model and Data Anal., p. 454-470, World Scientific Pub.
18. Pericchi L.R. and Walley P. (1991) Robust Bayesian credible intervals and prior ignorance. International Statistical Review 59(1), p. 1-23.
17. Espinosa R.A., Pericchi L.R. et al. (1991) Prognostic indicators of chronic Chagasic cardiopathy. International Journal of Cardiology 30, p. 195-202.
16. Atkinson A.C., Smith R.L. and Pericchi L.R. (1991) Grouped likelihood for the shifted power transformation. Journal of the Royal Statistical Society Series B (methodological), 53(2), p. 473-482.
15. Moreno E. and Pericchi L.R. (1990) Sensitivity of the Bayesian analysis to the prior: structural contaminations with specified quantiles of parametric families. Actas III Congreso Latinoamericano de Prob. y Estad. Mat., Publicaciones de la Soc. Bernoulli Latinoamericana, p. 143-158.
14. Walley P. and Pericchi L.R. (1990) One sided hypothesis testing with near-ignorant priors. Revista Brasileira de Probabilidade e Estatistica REBRAPE 4, p. 69-82.
13. Pereira C.A.B. and Pericchi L.R. (1990) Analysis of Diagnosability. Journal of the Royal Statistical Society Series C, Applied Statistics 39(2), p. 189-204.
12. Achcar J.A., Bolfarine H. and Pericchi L.R.(1989) Some applications of Bayesian methods in analysis of life data. Revista Brasileira de Probabilidade e Estatistica REBRAPE 3, p. 125-148.
11. Pericchi L.R. (1989) TEORIA ESTADISTICA DE DECISION Y ANALISIS BAYESIANO. Publications of the Instituto Venezolano de Investigaciones Cientificas (IVIC), ISBN 980-261-007-0, 145 pgs. (Invited Graduate Course, given in the Second National School of Mathematics, Venezuela (1989) 1st ed., in the Fourth Latin American Congress of Probability and Statistics, Mexico (1990) 2nd ed.), and "Avances Recientes en Estadistica Bayesiana y Econometria", Caracas, (1992, 3rd ed.).
10. Pericchi L.R. (1989) Sobre la inferencia y teoria de decision subjetivista-Bayesiana bajo probabilidades a priori imprecisas. Acta Cientifica Venezolana 40, p. 5-18.
9. Perez-Shael I., Pericchi L.R. et al.( 1989) Statistical analysis of a Rhesus Rotavirus vaccine trial to assess protective e_ect against diarrhea in Venezuelan children of 2-4 months of age. Interciencia, 14(4), p. 199-202.
8. Pericchi L.R. and Nazaret W. (1988) On being imprecise at the higher levels of a hierarchical linear model (invited discussion by Dr. A. Skene, University of Nottingham, U.K.). Bayesian Statistics 3, p. 361-375. Bernardo, J.M., De Groot M., Lindley D., Smith A.F.M. Editors. Oxford University Press. (Invited Conference).
7. Achcar J.A., Bolfarine H. and Pericchi L.R. (1987) Transformations of survival data to an extreme value distribution. The Statistician 36, p. 229-234.
6. Seoane R. and Pericchi L.R.(1986) Some new statistical methods for model choice and parameter estimation in statistical hydrology. Actas del sexto Symposium Brasileiro de Probalidade e Estatistica. (Invited Conference).
5. Pericchi L.R. and Rodriguez-Iturbe I. (1985) On the statistical analysis of oods, in "A Celebration of Statistics." (1985). Eds. A.C. Atkinson and S. Fienberg, Chapter 23, p. 511-541. Springer-Verlag.
4. Pericchi L.R. (1984) An alternative to the standard Bayesian procedure for discrimination between normal linear models. Biometrika 71(3), p. 575-586.
3. Pericchi L.R. and Rodriguez-Iturbe I. (1983) On some problems in Bayesian model choice in hydrology. The Statistician 32, p. 273-278.
2. Pericchi L.R. (1981) A Bayesian approach to transformations to Normality. Biometrika 68(1), p. 35-43.
1. Cordova J.R., Pericchi L.R. and Silvestre H. (1974) Optimizacion de la Altura de la Presa y Area de Desarrollo. Publicaciones del Ministerio de Obras Publicas, Venezuela.