标题： 加性保序回归 显示英文标题

标题： Additive isotone regression

摘要： 本文研究了非参数加性 isotone 回归模型中加性分量的最优估计问题。 结果表明，渐近意义上，在一阶近似下，如果其他分量已知，每个加性分量都可以像使用最小二乘估计器一样被估计得同样好。 用于计算估计器的算法采用了回代法。 证明了该算法的收敛性。 通过模拟实验还比较了有限样本性质。 显示英文摘要

摘要： This paper is about optimal estimation of the additive components of a nonparametric, additive isotone regression model. It is shown that asymptotically up to first order, each additive component can be estimated as well as it could be by a least squares estimator if the other components were known. The algorithm for the calculation of the estimator uses backfitting. Convergence of the algorithm is shown. Finite sample properties are also compared through simulation experiments.