ScholarGate
助手
Regression modelRegression / GLM

稳健分位数回归

稳健分位数回归在同时降低异常值影响的同时,估计响应变量的条件分位数。通过将标准分位数回归的不对称损失函数与有界影响或 M 估计量权重相结合,即使数据包含极端观测值或重尾误差分布,它也能提供可靠的分位数估计。

用 StatMind 应用即将推出视频即将推出Download slides

阅读完整方法

仅限会员

使用免费账户登录即可阅读本节。

登录

Method map

The neighbourhood of related methods — select a node to explore.

来源

  1. Koenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275
  2. Machado, J. A. F. (1993). Robust model selection and M-estimation. Econometric Theory, 9(3), 478–493. DOI: 10.1017/S0266466600007775

如何引用本页

ScholarGate. (2026, June 3). Robust Quantile Regression. ScholarGate. https://scholargate.app/zh/statistics/robust-quantile-regression

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

被引用于

ScholarGateRobust Quantile Regression (Robust Quantile Regression). 于 2026-06-15 检索自 https://scholargate.app/zh/statistics/robust-quantile-regression · 数据集: https://doi.org/10.5281/zenodo.20539026