Nonparametric empirical Bayes for the Dirichlet process mixture model
β Scribed by Jon D. McAuliffe; David M. Blei; Michael I. Jordan
- Publisher
- Springer US
- Year
- 2006
- Tongue
- English
- Weight
- 456 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0960-3174
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Let us consider a general population R. Each object belonging to the population R is characterized by a pair of correlated random vectors (& I). Both X and \_Y may be mixtures of discrete and continuous random variables. It will be assumed that our population R consists of k groups nl, ..., 3zk, whi
The Gumbel, or double exponential, probability distribution function is modified in order to characterize the failure times of a given system. The maximum likelihood (ML), minimum variance unbiased (MVU), Bayes, empirical Bayes, and non-parametric kernel density estimates of the reliability, failure