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Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics Softcover reprint of the original 2nd ed. 2016 edition
Eswar G. Phadia
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Prior Processes and Their Applications: Nonparametric Bayesian Estimation - Springer Series in Statistics Softcover reprint of the original 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.
327 pages, 1 Tables, color; 1 Illustrations, color; XVII, 327 p. 1 illus. in color.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 22 de abril de 2018 |
| ISBN13 | 9783319813707 |
| Editores | Springer International Publishing AG |
| Páginas | 327 |
| Dimensiones | 485 g |
| Lengua | English |
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