单指标期望模型的变量选择与去偏估计

Pub Date : 2022-02-02 DOI:10.1111/anzs.12348
Rong Jiang, Yexun Peng, Yufei Deng
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引用次数: 0

摘要

本文提出了单指标期望模型的惩罚非对称最小二乘估计。建立了该估计器的预言性。此外,利用消偏技术构造渐近正态的估计量,使有效置信区间的构造和假设检验成为可能。通过仿真研究和一个实际数据应用来说明所提出方法的有限样本性能。
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Variable selection and debiased estimation for single-index expectile model

This article develops a penalised asymmetric least squares estimator for single-index expectile model. The oracle property of the proposed estimator is established. Moreover, the debiasing technique is used to construct an estimator that is asymptotically normal, which enables the construction of valid confidence intervals and hypothesis testing. Simulation studies and one real data application are conducted to illustrate the finite sample performance of the proposed methods.

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