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伽马分布参数推断及其可靠性应用AI 解读

Lehmann and Scheffé have shown how to construct uniformly most powerful unbiased tests of certain hypotheses when the assumed distributions belong to an “exponential family.” The present paper is concerned with particular cases which arise from independent gamma variates with scale parameters θ1 and θ2. Conditional distributions are given which are appropriate for testing γ = γ0, where γ = c 1/θ1+c 2/θ2. As an application, suppose that a series system has two dissimilar…

伽马分布参数的若干推断及其可靠性应用AI 解读

Lehmann and Scheffé have shown how to construct uniformly most powerful unbiased tests of certain hypotheses when the assumed distributions belong to an “exponential family.” The present paper is concerned with particular cases which arise from independent gamma variates with scale parameters θ1 and θ2. Conditional distributions are given which are appropriate for testing γ = γ0, where γ = c 1/θ1+c 2/θ2. As an application, suppose that a series system has two dissimilar…