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Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics 2nd ed. 2016 edition
Eswar G. Phadia
Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics 2nd ed. 2016 edition
Eswar G. Phadia
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
Médias | Livres Hardcover Book (Livre avec dos et couverture rigide) |
Validé | 9 août 2016 |
ISBN13 | 9783319327884 |
Éditeurs | Springer International Publishing AG |
Pages | 327 |
Dimensions | 155 × 235 × 21 mm · 662 g |
Langue et grammaire | English |
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