Bayes-UC3M is a group of Bayesian researchers at the Universidad Carlos III de Madrid. The group members work in various aspects of Bayesian statistics and hold regular meetings to discuss themes of current interest.
· The renowned Bayesian statistician Prof. Fabrizio Ruggeri (CNR-Imati Milan) recently visited the Statistics Department at UC3M from May- October 2017.
· Fabrizio presented a short course on “Bayesian analysis of Poisson processes with applications in reliability” on Monday 9th and Tuesday 10th October from 11:00-13:00 and 15:00-17:00 both days in the Sala Costas Goutis, Room 10.0.23, UC3M, Campus de Getafe. The slides for Fabrizio’s talks are downloadable: day 1, day 2.
Group activities & Bayesian seminars
The Group holds periodic meetings to discuss a variety of current topics in Bayesian research. The next meetings are:
Recent seminars were:
o M.A. Vázquez, J. Míguez (2017). A robust scheme for distributed particle filtering in wireless sensors networks. Signal Processing, 131, 190-201.
o V. Elvira, J. Míguez, P.M. Djuric (2017). Adapting the Number of Particles in Sequential Monte Carlo Methods Through an Online Scheme for Convergence Assessment. IEEE Transactions on Signal Processing, 65, 1781-1794.
o S.B. Ramos, A. Taamouti, H. Veiga, C.-W. Wang (2017). Do investors price industry risk? Evidence from the cross-section of the oil industry. Journal of Energy Markets, 10, 79-108.
o F. Corona, J. de Diós Tena Horrillo, M. P. Wiper (2017). On the importance of the probabilistic model in identifying the most decisive games in a tournament. Journal of Quantitative Analysis in Sports, 13, 11-23.
o F. Liesen, J.M. Marín, C. Villa (2017). Objective Bayesian modelling of insurance risks with the skewed Student-t distribution. Applied Stochastic Models in Business and Industry, 33, 136-151
o J. de la Horra, J. M. Marín, M.T. Rodríguez Bernal (2017). Bayesian inference and data cloning in the calibration of population projection matrices. Communications in Statistics: Simulation and Computation, 46, 1669-1681.
o M. Leonti, G.I. Stafford, M. Dal Cero, S. Cabras, M.E. Castellanos, L. Casu, C.S. Weckerle (2017). Reverse Ethnopharmacology and Drug Discovery. Journal of Ethnopharmacology, 198, 417-431.
o G. Antoni, E. Marini, N. Curreli, V. Tuveri, O. Comandini, S. Cabras, S. Gabba, C. Madeddu, A. Crisafulli, A.C. Rinaldi (2017). Energy expenditure in caving. PloS ONE, 12, e0170853.
o M.S. Geck, S. Cabras, L. Casu, A.J. Reyes García, M. Leonti (2017) The taste of heat: How humoral qualities act as a cultural filter for chemosensory properties guiding herbal medicine. Journal of Ethnopharmacology, 198, 499-515.
o Fabrizio Liesen: now at University of Kent, UK.
o Gabriel Nuñez Antonio: now at Universidad Autónoma Metropolitana, Iztapalapa, Mexico.
o Audra Virbickaite: now at University of Konstanz, Germany.
o Workshop: Métodos Bayesianos'17.Madrid. 7-8, November 2017. U. Complutense de Madrid, Spain.
o Workshop: BayesComp 2018. 26-28 March, 2018. Barcelona, Spain.
o Conference: 2018 ISBA World Meeting. 24-29 June, 2018. Edinburgh, UK
o ISBA is the International Society for Bayesian Analysis.
o Bayesian Methods Research Group at the Universidad Complutense de Madrid.
o Bayesian Inference is the premier Bayesian journal.
o Sequential Monte Carlo Methods & Particle Filters Resources, with papers, codes, ...
o Christian Robert’s blog has lots of information on new Bayesian ideas.
o Understanding Uncertainty by David Spiegelhalter.
o Bayesblog by Mark Phillips.
o Stan is a modern Gibbs sampling / MCMC package.
o OpenBUGS is another useful Gibbs/MCMC package.
o JAGS is just another Gibbs sampling package.
o JASP is a general stats package quite like SPSS and with a lot of integrated Bayesian analyses.
o R has many Bayesian analysis tools:
§ Laplaces Demon is an integrated Bayesian inference pack.
§ MCMCpack allows the running of general MCMC algorithms.
§ DPpackage implements various Bayesian nonparametric algorithms.
§ abc runs approximate Bayesian computation algorithms.
Last update: 8th November, 2017.