A Bayesian Semiparametric Latent Variable Model for Mixed Responses

By Ludwig Fahrmeir, Alexander Raach. 2007

84 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/25aefb4cf6c35fca69057e1022c8652567662279

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. Ming-Chung Yang
2. David B. Dunson
3. Qiang Yang
4. Yu Zhang
5. Lawrence Carin
6. David M. Blei
7. Enrique ter Horst
8. Abel Rodríguez

In Statistics and Probability

1. Ming-Chung Yang
2. David B. Dunson
3. Daniel M. McNeish
4. Lawrence Carin
5. David M. Blei
6. Natalya Pya
7. Simon N. Wood
8. Daniele Durante

Citations in the corpus

• The Dynamics of State Policy Liberalism, 1936–2014 (2016, unknown): “…variable j, the conditional probability that y⇤jst ⇠ N( j✓st ↵jt, 1) is observed as yjst = k is Pr(⌧j,k 1 y ⇤ jst ⌧jk | j✓st ↵jt) =Pr(y⇤jst ⌧jk | j✓st ↵jt) Pr(y⇤jst ⌧j,k 1 | j✓st ↵jt) = (⌧jk [ j✓st ↵jt]) (⌧j,k 1 [ j✓st ↵jt]), (2) where is the standard normal CDF (Fahrmeir and Raach 2007, 329).”
• Bayesian Semiparametric Structural Equation Models with Latent Variables (2010, methodology): “Key Words: Dirichlet process; Factor analysis; Latent class; Latent trait; Mixture model; Nonparametric Bayes; Parameter expansion.”