论文标题
参数模态回归与协变量中的误差
Parametric Modal Regression with Error in Covariates
论文作者
论文摘要
提出了一个推理过程，以在模态回归模型中提供一致的参数估计量，该模型易于测量误差。开发了基于分数的诊断工具利用参数引导程序，以评估回归模型中施加的参数假设的充分性。提出的估计方法和诊断工具应用于模拟实验和现实世界应用程序中生成的合成数据，以证明其实现和性能。这些经验示例说明了基于模态回归模型推断响应与协变量之间的关联时，充分考虑了容易出错的协变量的测量误差的重要性，该模态模型特别适合偏斜且重型响应数据。
An inference procedure is proposed to provide consistent estimators of parameters in a modal regression model with a covariate prone to measurement error. A score-based diagnostic tool exploiting parametric bootstrap is developed to assess adequacy of parametric assumptions imposed on the regression model. The proposed estimation method and diagnostic tool are applied to synthetic data generated from simulation experiments and data from real-world applications to demonstrate their implementation and performance. These empirical examples illustrate the importance of adequately accounting for measurement error in the error-prone covariate when inferring the association between a response and covariates based on a modal regression model that is especially suitable for skewed and heavy-tailed response data.
