Browsing by Subject "Factor analysis"
Now showing items 1-5 of 5
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Bayesian Gaussian Copula Factor Models for Mixed Data.
(J Am Stat Assoc, 2013-06-01)Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent ... -
Bayesian Modeling and Computation for Mixed Data
(2012)Multivariate or high-dimensional data with mixed types are ubiquitous in many fields of studies, including science, engineering, social science, finance, health and medicine, and joint analysis of such data entails both ... -
Data-driven investigations of disgust
(2019)Disgust features prominently in many facets of human life, from dining etiquette to spider phobia to genocide. For some applications, such as public health campaigns, it might be desirable to know how to increase disgust, ... -
Easy and Efficient Bayesian Infinite Factor Analysis
(2020)Bayesian latent factor models are key tools for modeling linear structure in data and performing dimension reduction for correlated variables. Recent advances in prior specification allow the estimation of semi- ... -
New tools for Bayesian clustering and factor analysis
(2022)Traditional model-based clustering faces challenges when applied to mixed scale multivariate data, consisting of both categorical and continuous variables. In such cases, there is a tendency for certain variables to overly ...
