Robustness to outliers in location–scale parameter model using log-regularly varying distributions
利用对数正则变动分布实现位置—尺度模型的离群值稳健性
Estimating the location and scale parameters is common in statistics, using, for instance, the well-known sample mean and standard deviation. However, inference can be contaminated by the presence of outliers if modeling is done with light-tailed distributions such as the normal distribution. In this paper, we study robustness to outliers in location–scale parameter models using both the Bayesian and frequentist approaches. We find sufficient conditions (e.g., on tail…