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B0740
Title: Power logit regression for modeling bounded data Authors:  Silvia Ferrari - University of Sao Paulo (Brazil) [presenting]
Francisco F Queiroz - University of Sao Paulo (Brazil)
Abstract: The main purpose is to introduce a new class of regression models for bounded continuous data, commonly encountered in applied research. The models, named the power logit regression models, assume that the response variable follows a distribution in a wide, flexible class of distributions with three parameters, namely the median, a dispersion parameter and a skewness parameter. A comprehensive set of tools is offered for likelihood inference and diagnostic analysis, and the new R package PLreg is introduced. Applications with real and simulated data show the merits of the proposed models, the statistical tools, and the computational package.