Models based on the Kumaraswamy law are used with variables that assume values in (0, 1). In some cases, however, the data contain zeros and/or ones, that is, there is data inflation. We introduce a class of regression models that can be used with such inflated data, namely: the class of inflated Kumaraswamy regression models. We consider inflation at zero, at one, and at both zero and one. We introduce the model and provide closed-form expressions for its score vector and Fisher's information matrix. The proposed model is used to evaluate the impacts of different conditioning variables on the proportion of people who live in households with inadequate water supply and sewage in Brazilian municipalities. Our results reveal that policies directed to increasing the population share with college education in places where it is low are particularly effective in reducing the prevalence of people who live under inadequate sanitation conditions.

中文翻译：

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夸大 Kumaraswamy 回归并应用于巴西的供水和卫生

基于 Kumaraswamy 定律的模型与假定值在 (0, 1) 中的变量一起使用。然而，在某些情况下，数据包含零和/或一，即存在数据膨胀。我们介绍了一类可用于此类膨胀数据的回归模型，即：膨胀型 Kumaraswamy 回归模型类。我们考虑通货膨胀为零、一以及零和一。我们介绍了该模型并为其得分向量和 Fisher 信息矩阵提供了封闭形式的表达式。所提出的模型用于评估不同条件变量对巴西城市供水和污水不足的家庭人口比例的影响。