On Optimal Asymptotic Tests of Composite Statistical Hypotheses

Abstract

A locally asymptotically most powerful test for a composite hypothesis $H:\xi = \xi_0$ has been developed for the case where the observable random variables $\{X_{nk}, k = 1, 2, \cdots, n\}$ are independently but not necessarily identically distributed. However, their distributions depend on $s + 1$ parameters, one being $\xi$ under test and the other being a vector $\theta = (\theta_1, \cdots, \theta_s)$ of nuisance parameters. The theory is illustrated with an example from the field of astronomy.