Abstract

Based on the approach of left and right kernel smoothing with unilateral kernel function, we, in this paper, define estimators of change point and jump size in nonparametric regression model with response missing at random. It is shown that the change point estimator is n-consistent and converges to the smallest maximizer of one-dimensional bilateral compound Poisson process, the jump size estimator is asymptotically normal. A simulation study is conducted to investigate the finite sample behavior for the proposed methods.

中文翻译：

---

回归模型中的变化点估计，随机缺少响应

摘要

基于具有单边核函数的左右核平滑方法，我们在非参数回归模型中定义了随机缺少响应的变化点和跳跃大小的估计量。结果表明，变化点估计量是n-一致的，并且收敛到一维双边复合泊松过程的最小极大值，跳变大小估计量是渐近正态的。进行了仿真研究，以研究所提出方法的有限样本行为。