In this work, we introduce a regression model for double-bounded variables in the interval (0, 1) following a Kumaraswamy distribution. The model resembles a generalized linear model, in which the response’s median is modeled by a regression structure through the asymmetric Aranda-Ordaz parametric link function. We consider the maximum likelihood approach to estimate the regression and the link function parameters altogether. We study large sample properties of the proposed maximum likelihood approach, presenting closed-form expressions for the score vector as well as the observed and Fisher information matrices. We briefly present and discuss some diagnostic tools. We provide numeric evaluation of the finite sample inferences to show the performance of the estimators. Finally, to exemplify the usefulness of the methodology, we present and explore an empirical application.

在这项工作中，我们为遵循Kumaraswamy分布的区间（0，1）中的双界变量引入了回归模型。该模型类似于广义线性模型，其中响应的中位数通过不对称Aranda-Ordaz参数链接函数的回归结构建模。我们考虑使用最大似然方法来估计回归和链接函数参数。我们研究了拟议的最大似然方法的大型样本属性，给出了分数向量以及观测值和Fisher信息矩阵的闭式表达式。我们简要介绍并讨论一些诊断工具。我们提供有限样本推论的数值评估，以显示估计器的性能。最后，为了说明该方法的实用性，