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Focusing on statistical theory, this graduate textbook is designed for Ph.D. candidates in statistics. It begins with a concise overview of measure-theoretic probability, followed by foundational concepts in statistical decision theory and inference. The subsequent chapters delve into crucial topics such as unbiased estimation, parametric and nonparametric estimation, hypothesis testing, and confidence sets. Each chapter is enriched with numerous exercises, offering students both practice and additional theoretical insights.
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Mathematical Statistics, Jun Shao
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- 2010
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