James-Stein-Type Estimators in Large Samples With Application to the Least Absolute Deviations Estimator

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A Semiparametric Basis for Combining Estimation Problems Under Quadratic Loss (2004, background): “Ō ¡ Q̄ / C Q̄ : Given this base, Kim and White (2001) provided an expression for the asymptotic risk and bias of Green–Strawderman (GS) Stein-type estimators that also applies to cases of correlated estimators and presented some asymptotic estimation results for the case where both estimators are…”
Optimal Weight Choice for Frequentist Model Average Estimators (2011, background): “…and β̂r (i.e., all the regressors in Z are either in or out), then minimizing (11) with respect to (a,b) leads to the estimator β̂js = { 1 − σ̂ 2 tr(Q′Q) ‖β̂u − β̂r‖2 } β̂u + σ̂ 2 tr(Q′Q) ‖β̂u − β̂r‖2 β̂r, (12) which turns out to be the James–Stein type estimator studied by Kim and White (2001).”
Focused information criterion and model averaging for generalized additive partial linear models (2011, methodology): “ one is free to consider only a few relevant submodels (unnecessarily nested or ordered) to be used in the model selection or averaging. A special example is the James–Stein-type estimator studied by Kim and White (2001), which is a weighted summand of the estimators based on the reduced model (du,S”