Mixed and Mixture Regression Models for Continuous Bounded Responses Using the Beta Distribution

By J. Verkuilen, Michael Smithson. 2012

133 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6adb99f38ae76fda52e6e0eb3c705cb50c42c2c8

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. C. Bayes
2. Mário de Castro
3. Jorge L. Bazán
4. M. H. Alava
5. L. Gray

In Statistics and Probability

1. Mário de Castro
2. C. Bayes
3. Jorge L. Bazán
4. M. H. Alava
5. L. Gray
6. Gauss Moutinho Cordeiro
7. Edwin M. M. Ortega

Citations in the corpus

• A quantile parametric mixed regression model for bounded response variables (2017, methodology): “For these situations, [36] and [13] proposed a beta mixed regression model considering random effects in both the mean and the dispersion parameters.”
• A Command for Fitting Mixture Regression Models for Bounded Dependent Variables Using the Beta Distribution (2018, methodology): “A good procedure to follow in this case is to start by estimating a model with constant precision as a stepping stone for the full model (Verkuilen and Smithson 2012).”