| When  there  is  uncertainty  concerning  the  appropriate  statistical  model  to  use  in  representing the data sampling process and corresponding estimators, we consider a basis for optimally combining estimation  problems.    In the context of the multivariate linear  statistical model, we consider a semi-parametric  Stein-like (SPSL) estimator, ...that shrinks to a random data-dependent vector and, under quadratic loss, has superior performance relative to the conventional least squares estimator. The relationship of the SPSL estimator to the family of Stein estimators is noted and risk dominance extensions between correlated estimators are demonstrated.  As an application we consider the problem of a possibly ill-conditioned design matrix and devise... |