Loss Functions for Detecting Outliers in Panel Data
用于面板数据异常值检测的损失函数
The detection of outliers is of critical importance in the assurance of data quality. Outliers may exist in observed data or in data derived from these observed data, such as estimates and forecasts. An outlier may indicate a problem with its data generation process or may simply be a true, but unusual, statement about the world. Without making any distributional assumptions, we proposes the use of loss functions to detect these outliers in panel data. Part I covers…