Inflated beta distributions

By Raydonal Ospina, Silvia L. P. Ferrari. 2007

391 citations recorded by the source corpus.

This paper considers the issue of modeling fractional data observed on [0,1), (0,1] or [0,1]. Mixed continuous-discrete distributions are proposed. The beta distribution is used to describe the continuous component of the model since its density can have quite different shapes depending on the values of the two parameters that index the distribution. Properties of the proposed distributions are examined. Also, estimation based on maximum likelihood and conditional moments is discussed. Finally, practical applications that employ real data are presented.

Subfields: Artificial Intelligence, Modeling and Simulation, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/386c413d116cf9f91e969924d666d22ceb1614a3

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. Raydonal Ospina
2. Silvia L. P. Ferrari
3. Annamaria Guolo
4. Cristiano Varin
5. Jacob C. Douma
6. J. Weedon

In Modeling and Simulation

1. Raydonal Ospina
2. Silvia L. P. Ferrari

In Statistics and Probability

1. Raydonal Ospina
2. Silvia L. P. Ferrari
3. Annamaria Guolo
4. Cristiano Varin
5. Jacob C. Douma
6. J. Weedon
7. C. Bayes
8. Jorge L. Bazán

Citations in the corpus

• A general class of zero-or-one inflated beta regression models (2011, methodology): “Other properties of this distribution can be found in Ospina & Ferrari (2010).”