论文标题
分布（单）索引模型
Distributional (Single) Index Models
论文作者
论文摘要
分布（单）索引模型（DIM）是用于分布回归的半参数模型，即给定协变量的条件分布的估计。该方法是经典单个指数模型的组合，用于估计给定协变量的响应的条件平均值和等渗分布回归。该索引的模型是参数，而条件分布在随机排序约束下进行非参数估计。我们显示了估计器的一致性，并将其应用于重症监护病房中患者的住院时间（LOS）的高度挑战性数据集。我们使用该模型为个别患者的LOS提供熟练和校准的概率预测，这表现优于文献中的可用方法。
A Distributional (Single) Index Model (DIM) is a semi-parametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method is a combination of classical single index models for the estimation of the conditional mean of a response given covariates, and isotonic distributional regression. The model for the index is parametric, whereas the conditional distributions are estimated non-parametrically under a stochastic ordering constraint. We show consistency of our estimators and apply them to a highly challenging data set on the length of stay (LoS) of patients in intensive care units. We use the model to provide skillful and calibrated probabilistic predictions for the LoS of individual patients, that outperform the available methods in the literature.
