Parametric Statistical Inference by James K. Lindsey
This concise graduate-level text develops the theory and practice of parametric statistical inference, focusing on likelihood-based methods and their large-sample properties. It covers estimation (consistency, asymptotic normality and efficiency), information and sufficiency, hypothesis testing using score, Wald and likelihood-ratio approaches, and the role of exponential families, with attention to practical examples and exercises that illustrate the application of the theoretical results.
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