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Large Deviations of Continuous Regular Conditional Probabilities

机译:持续常规条件概率的大偏差

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We study product regular conditional probabilities under measures of two coordinates with respect to the second coordinate that are weakly continuous on the support of the marginal of the second coordinate. Assuming that there exists a sequence of probability measures on the product space that satisfies a large deviation principle, we present necessary and sufficient conditions for the conditional probabilities under these measures to satisfy a large deviation principle. The arguments of these conditional probabilities are assumed to converge. A way to view regular conditional probabilities as a special case of product regular conditional probabilities is presented. This is used to derive conditions for large deviations of regular conditional probabilities. In addition, we derive a Sanov-type theorem for large deviations of the empirical distribution of the first coordinate conditioned on fixing the empirical distribution of the second coordinate.
机译:我们研究了在两种坐标的测量下的常规条件概率,这是关于第二个坐标对第二个坐标的边缘的支持弱连续的第二坐标。 假设在满足大偏差原理的产品空间上存在一系列概率测量,我们对这些措施下的条件概率存在必要和充分的条件,以满足大的偏差原理。 假设这些条件概率的参数收敛。 提出了一种观看定期条件概率作为产品定期条件概率的特殊情况的方法。 这用于导出常规条件概率的大偏差的条件。 此外,我们派生了一个SANOV型定理,用于对修复第二坐标的经验分布的第一坐标的经验分布的大偏差。

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