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Bayesian Nonparametrics (Springer Series in Statistics) by Jayanta K. Ghosh; Paul R. Rosenbaum; R.V. Ramamoorthi is a mathematics available to read on EtoBox.

What is Bayesian Nonparametrics (Springer Series in Statistics) about?

Bayesian Nonparametrics Has Grown Tremendously In The Last Three Decades, Especially In The Last Few Years. This Book Is The First Systematic Treatment Of Bayesian Nonparametric Methods And The Theory Behind Them. While The Book Is Of Special Interest To Bayesians, It Will Also Appeal To Statisticians In General Because Bayesian Nonparametrics Offers A Whole Continuous Spectrum Of Robust Alternatives To Purely Parametric And Purely Nonparametric Methods Of Classical Statistics. The Book Is Primarily Aimed At Graduate Students And Can Be Used As The Text For A Graduate Course In Bayesian Nonparametrics. Though The Emphasis Of The Book Is On Nonparametrics, There Is A Substantial Chapter On Asymptotics Of Classical Bayesian Parametric Models. Jayanta Ghosh Has Been Director And Jawaharlal Nehru Professor At The Indian Statistical Institute And President Of The International Statistical Institute. He Is Currently Professor Of Statistics At Purdue University. He Has Been Editor Of Sankhya And Served On The Editorial Boards Of Several Journals Including The Annals Of Statistics. Apart From Bayesian Analysis, His Interests Include Asymptotics, Stochastic Modeling, High Dimensional Model

Who reads Bayesian Nonparametrics (Springer Series in Statistics)?

Author

Jayanta K. Ghosh; Paul R. Rosenbaum; R.V. Ramamoorthi

Publisher

Springer

Published

2003

Language

EN

ISBN

9780387955377

Category

mathematics

Subjects

Mathematics, Stem

Rating

5 / 5 (2 ratings)

Updated

2026-03-14