文章基本信息

标题：On Bias Correction in a Class of Inflated Beta Regression Models
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作者：Raydonal Ospina ; Silvia Ferrari
期刊名称：International Journal of Statistics and Probability
印刷版ISSN：1927-7032
电子版ISSN：1927-7040
出版年度：2012
卷号：1
期号：2
页码：269
DOI：10.5539/ijsp.v1n2p269
出版社：Canadian Center of Science and Education
摘要：Inflated beta regression models bear practical applicability in modeling rates and proportions measured continuously in the presence of zeros and/or ones. In this article, the second-order bias of maximum likelihood estimators for zero-or-one inflated beta regression model parameters is derived. This enables one to obtain corrected estimators that are approximately unbiased. Numerical results exhibit that corrected estimators show better performance in terms of mean-square error and bias when compared to maximum likelihood estimators.