Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics - Eswar G. Phadia - Books - Springer International Publishing AG - 9783319327884 - August 9, 2016
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Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics 2nd ed. 2016 edition

Eswar G. Phadia

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Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics 2nd ed. 2016 edition

After an overview of different prior processes, it examines the now pre-eminent Dirichlet process and its variants including hierarchical processes, then addresses new processes such as dependent Dirichlet, local Dirichlet, time-varying and spatial processes, all of which exploit the countable mixture representation of the Dirichlet process.

344 pages, 1 colour illustrations, 1 colour tables, biography

Media Books     Hardcover Book   (Book with hard spine and cover)
Released August 9, 2016
ISBN13 9783319327884
Publishers Springer International Publishing AG
Pages 327
Dimensions 155 × 235 × 21 mm   ·   662 g
Language English  
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