Bayesian nonparametric and semiparametric mixture models have become extremely popular in the last 10 years because they provide flexibility and interpretability while preserving computational simplicity. This book is a contribution to this growing literature, discussing the design of models for collections of distributions and their application to density estimation and nonparametric regression. All methods introduced in this book are discussed in the context of complex scientific applications in public health, epidemiology and finance.
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Abel Rodriguez was born in Caracas, Venezuela, on July 16, 1975. After graduating with B.S. degrees in Engineering and Law, he completed a M.S. in Statistics in 2000. In 2003 he returned to academia to pursue a Ph.D. in Statistics at Duke University. He is currently Assistant Professor at the University of California, Santa Cruz.
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Taschenbuch. Condition: Neu. Some Advances in Bayesian Nonparametric Modeling | Nested Dirichlet process and nonparametric regression | Abel Rodriguez | Taschenbuch | 168 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838300122 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 101638449
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Bayesian nonparametric and semiparametric mixture models have become extremely popular in the last 10 years because they provide flexibility and interpretability while preserving computational simplicity. This book is a contribution to this growing literature, discussing the design of models for collections of distributions and their application to density estimation and nonparametric regression. All methods introduced in this book are discussed in the context of complex scientific applications in public health, epidemiology and finance.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 168 pp. Englisch. Seller Inventory # 9783838300122
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bayesian nonparametric and semiparametric mixture models have become extremely popular in the last 10 years because they provide flexibility and interpretability while preserving computational simplicity. This book is a contribution to this growing literature, discussing the design of models for collections of distributions and their application to density estimation and nonparametric regression. All methods introduced in this book are discussed in the context of complex scientific applications in public health, epidemiology and finance. Seller Inventory # 9783838300122