<p><strong>课程介绍：</strong></p> <p>本课程为统计推断提供了理论基础。 在决策理论框架中讨论了推理中的三个主要目标（估计，置信集构造和假设检验）。 重点放在频率论和贝叶斯方法上。</p> <p>对参数，非参数和鲁棒程序进行了比较和对比。 针对固定样本大小和渐近意义讨论了推理的最优性。 还引入了高阶渐近方法。 从理论上和数字上说明了诸如自举之类的计算密集型程序。 将讨论许多说明性示例和实际应用。</p>
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