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首页> 外文期刊>Australian & New Zealand journal of statistics >Modal non-linear regression in the presence of Laplace measurement error
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Modal non-linear regression in the presence of Laplace measurement error

机译：Laplace测量误差存在下模态非线性回归

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Summary In this paper, we propose a robust estimation procedure for a class of non‐linear regression models when the covariates are contaminated with Laplace measurement error, aiming at constructing an estimation procedure for the regression parameters which are less affected by the possible outliers, and heavy‐tailed underlying distribution, as well as reducing the bias introduced by the measurement error. Starting with the modal regression procedure developed for the measurement error‐free case, a non‐trivial modification is made so that the modified version can effectively correct the potential bias caused by measurement error. Large sample properties of the proposed estimate, such as the convergence rate and the asymptotic normality, are thoroughly investigated. A simulation study and real data application are conducted to illustrate the satisfying finite sample performance of the proposed estimation procedure.
机译：发明内容本文提出了一类非线性回归模型的稳健估计程序，当协变量被拉普拉斯测量误差污染时，旨在构建受可能性异常值影响较小的回归参数的估计过程，以及重型底层的分布，以及减少测量误差引入的偏差。从为测量无误误差开发的模态回归过程开始，使得修改的版本可以有效地校正由测量误差引起的电位偏差。彻底研究了所提出的估计的大样本性质，例如收敛速度和渐近常态。进行仿真研究和实际数据应用以说明所提出的估计程序的满意有限样本性能。

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