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用不完美模型解释统计证据：稳健调整似然函数AI 解读

Summary The strength of statistical evidence is measured by the likelihood ratio. Two key performance properties of this measure are the probability of observing strong misleading evidence and the probability of observing weak evidence. For the likelihood function associated with a parametric statistical model, these probabilities have a simple large sample structure when the model is correct. Here we examine how that structure changes when the model fails. This leads to…

有限总体抽样理论的一种传统路径AI 解读

The main objective of this work is to relate classical inference and sampling theory (and current sampling practice) to recent advances toward formalizing and unifying the theory of sampling from finite populations. It is pointed out that the use of definitions which coincide with what seem to be the traditional notions of simple random sampling, and post-stratification (stratification after sampling) leads to the solution of such riddles which appear in the more recent…