Hybrid confidence intervals for informative uniform asymptotic inference after model selection
模型选择后兼具信息量与一致渐近有效性的混合置信区间
Abstract I propose a new type of confidence interval for correct asymptotic inference after using data to select a model of interest without assuming any model is correctly specified. This hybrid confidence interval is constructed by combining techniques from the selective inference and post-selection inference literatures to yield a short confidence interval across a wide range of data realizations. I show that hybrid confidence intervals have correct asymptotic coverage,…