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.

翻译：提议了一个推论程序,以提供对模式回归模型参数的一致估计,同时采用易于测量误差的共变法; 开发一个以分数为基础的诊断工具,利用参数靴来评估对回归模型施加的参数假设的充分性; 将拟议的估算方法和诊断工具应用于模拟实验产生的合成数据以及现实应用中的数据,以证明其实施和性能; 这些经验实例表明,在根据特别适合偏斜和重尾反应数据的模式模型推断反应和共变法之间的关联时,必须充分计算易出误差的共变法误差。