Abstract
AbstractWe develop a saddle‐point approximation for the marginal density of a real‐valued function p(), where is a general M‐estimator of a p‐dimensional parameter, that is, the solution of the system {n‐1ljl (Yl,) = 0}j=1,…,p. The approximation is applied to several regression problems and yields very good accuracy for small samples. This enables us to compare different classes of estimators according to their finite‐sample properties and to determine when asymptotic approximations are useful in practice.
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