Bayesian Semiparametric Structural Equation Models with Latent Variables

By Ming-Chung Yang, David B. Dunson. 2010

86 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b460064c467cbab81ac984b8eac79e42be37e4ed

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Holger Brandt
2. Augustin Kelava
3. Benjamin Nagengast

In Molecular Biology

1. Holger Brandt
2. Augustin Kelava
3. Benjamin Nagengast

In Statistics and Probability

1. Holger Brandt
2. Augustin Kelava
3. Benjamin Nagengast

Citations in the corpus

• A Nonlinear Structural Equation Mixture Modeling Approach for Nonnormally Distributed Latent Predictor Variables (2014, methodology): “…have highly desirable properties in terms of approximating an arbitrary multivariate distribution of the latent predictors, but on the other hand, the interpretation of the latent variables and identifiability require centering procedures for discrete and continuous mixtures (Yang & Dunson, 2010).”