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Isaac Newton Institute for Mathematical Sciences

Bayesian Nonparametric Regression: Theory, Methods and Applications

Papers produced by Participants

Preprint No. Author(s) Title and publication details
IP07185 O Papaspiliopoulas Filtering coupled SDEs partially observed at high frequency
IP07187 F Quintana,A Jara,P Mueller Nonparametric Bayesian data analysis
IP07188 F Quintana, A Jara Some practical aspects of nonparametric Bayesian models
IP07189 F Quintana,A Jara,S MacEachern Covariate dependant Polya trees
IP07190 J Griffin, C Holmes Bayesian nonparametric calibration with application to spatial epidemiology
IP07191 J Griffin Normalized shot-noise random measures
IP07192 O Papaspiliopoulas Filtering coupled SPTs partially observed at high frequency
IP07198 P Mueller,F Quintana,A Jara Bayesian data analysis
IP07199 S MacEachern, A Jara, W Johnson Dependant Polva tree models
IP07200 A MacEachern,Y Kim Random effects surfaces
IP07201 S MacEachern, N Hjort Bayesian local likelihood
IP07202 S MacEachern,P Mueller Dependent Dirichlet processes - a taxonomy
IP07207 A Martinelli, M Ruggiero, SG Walker A note on convergence rates for posterior distributions via large deviations techniques
IP07211 NL Hjort, C Holmes,S Walker Introduction to Bayesian Nonparametrics
IP07212 NL Hjort, P de Blasi Semiparametric competing risks models
IP07213 NL Hjort,S MacEachern Bayesian local linear regression
IP07214 NL Hjort, Y Kim Beta processes: a review
IP07215 P de Blasi,LF James,J Lau Bayesian nonparametric estimation and consistency of mixed multinomial logit choice models
IP07216 P de Blasi, NL Hjort Regression analysis for competing risk data