期刊
COMPUTATIONAL STATISTICS & DATA ANALYSIS
卷 56, 期 6, 页码 1609-1623出版社
ELSEVIER
DOI: 10.1016/j.csda.2011.10.005
关键词
Continuous proportions; Zero-or-one inflated beta distribution; Fractional data; Maximum likelihood estimation; Diagnostics; Residuals
资金
- FAPESP/Brazil
- CNPq/Brazil
This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.
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