论文标题
条件分布功能和条件分位数的随机森林估计
Random forest estimation of conditional distribution functions and conditional quantiles
论文作者
论文摘要
我们提出了对有条件分布函数的两个现实估计量和使用随机森林的有条件分位数的理论研究。估算过程使用在构造森林时从原始数据集生成的引导程序样品。重新使用引导样品来定义第一个估计器，而第二个估计器仅需要原始样品，一旦建造了森林。我们证明，条件分布函数的两个提出的估计值在A.S.据我们所知，这是一致性的第一个证明，包括引导部分。我们还在数值示例上说明了估计过程。
We propose a theoretical study of two realistic estimators of conditional distribution functions and conditional quantiles using random forests. The estimation process uses the bootstrap samples generated from the original dataset when constructing the forest. Bootstrap samples are reused to define the first estimator, while the second requires only the original sample, once the forest has been built. We prove that both proposed estimators of the conditional distribution functions are consistent uniformly a.s. To the best of our knowledge, it is the first proof of consistency including the bootstrap part. We also illustrate the estimation procedures on a numerical example.
