Bayesian Analysis of the Heterogeneity Model
By Sylvia Frühwirth-Schnatter, Regina Tüchler, Thomas Otter. 2004
69 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c6915ba9e2cdb47e161e90a3a3c33b02809fea17
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In Artificial Intelligence
In Statistics and Probability
Citations in the corpus
- Bayesian Statistics and Marketing (2005, background): “, the components primarily differ in V , not ̄ , then the prior can lead to a chain that is slow to converge (Frühwirth-Schnatter et al. 2003).”
- Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach (2010, background): “In this line, different measures have been implemented in the literature to avoid identifiability problems (see Lenk and DeSarbo 2000; Fruhwirth-Schnatter et al 2004 ).”
- Estimating Marginal Likelihoods for Mixture and Markov Switching Models Using Bridge Sampling Techniques (2004, unknown): “This class encompasses many important mixture and switching models such as univariate and multivariate normal mixture models, mixtures of random effects models (Lenk and DeSarbo 2000; Frühwirth-Schnatter et al. 2004), and the Markov switching autoregressive model (McCulloch and Tsay 1994), but also ”