Local asymptotic normality (LAN) is a concept used in the field of statistics and estimation theory, particularly in the context of statistical inference and asymptotic theory. It provides a framework to analyze the behavior of maximum likelihood estimators (MLEs) and similar statistical procedures in large samples.
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A regular statistical model is locally asymptotically normal at when its log-likelihood ratio under local shifts has the expansion