A Semiparametric Basis for Combining Estimation Problems Under Quadratic Loss
二次损失下组合估计问题的半参数基础
When there is uncertainty concerning the appropriate statistical model-estimator to use in representing the data sampling process, we consider a basis for optimally combining estimation problems. The objective is to produce natural adaptive estimators that are free of subjective choices and tuning parameters. In the context of two competing multivariate linear statistical models–estimators, we demonstrate a semiparametric Stein-like (SPSL) estimator, , that, under quadratic…