Bayesian Analysis of Mixtures of Factor Analyzers
نویسندگان
چکیده
For Bayesian inference on the mixture of factor analyzers, natural conjugate priors on the parameters are introduced, and then a Gibbs sampler that generates parameter samples following the posterior is constructed. In addition, a deterministic estimation algorithm is derived by taking modes instead of samples from the conditional posteriors used in the Gibbs sampler. This is regarded as a maximum a posteriori estimation algorithm with hyperparameter search. The behaviors of the Gibbs sampler and the deterministic algorithm are compared on a simulation experiment.
منابع مشابه
A mixture of generalized hyperbolic factor analyzers
The mixture of factor analyzers model, which has been used successfully for the model-based clustering of high-dimensional data, is extended to generalized hyperbolic mixtures. The development of a mixture of generalized hyperbolic factor analyzers is outlined, drawing upon the relationship with the generalized inverse Gaussian distribution. An alternating expectation-conditional maximization a...
متن کاملModel Selection for Mixtures of Factor Analyzers via Hierarchical BIC
Bayesian information criterion (BIC) is a common model selection criterion for mixtures of factor analyzers (MFA). However, it is found that BIC penalizes each factor analyzer implausibly using the whole sample size. In this paper, we propose a new criterion for MFA called hierarchical BIC (H-BIC). Formally, the main difference from BIC is that H-BIC penalizes each factor analyzer using its own...
متن کاملExtending mixtures of multivariate t-factor analyzers
Model-based clustering typically involves the development of a family of mixture models and the imposition of these models upon data. The best member of the family is then chosen using some criterion and the associated parameter estimates lead to predicted group memberships, or clusterings. This paper describes the extension of the mixtures of multivariate t-factor analyzers model to include co...
متن کاملMixtures of skew-t factor analyzers
In this paper, we introduce a mixture of skew-t factor analyzers as well as a family of mixture models based thereon. The mixture of skew-t distributions model that we use arises as a limiting case of the mixture of generalized hyperbolic distributions. Like their Gaussian and t-distribution analogues, our mixture of skew-t factor analyzers are very well-suited to the model-based clustering of ...
متن کاملMixtures of Bayesian joint factor analyzers for noise robust automatic speech recognition
This paper investigates a noise robust approach to automatic speech recognition based on a mixture of Bayesian joint factor analyzers. In this approach, noisy features are modeled by two joint groups of factors accounting for speaker and noise variabilities which are estimated by clean and noisy speech respectively. The factors form an overcomplete dictionary with a redundant representation. Au...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Neural computation
دوره 13 5 شماره
صفحات -
تاریخ انتشار 2001