Replication and Its Application to Weak Convergence

C. Dong, M. Kouritzin
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引用次数: 1

Abstract

Herein, a methodology is developed to replicate functions, measures and stochastic processes onto a compact metric space. Many results are easily established for the replica objects and then transferred back to the original ones. Two problems are solved within to demonstrate the method: (1) Finite-dimensional convergence for processes living on general topological spaces. (2) New tightness and relative compactness criteria are given for the Skorokhod space $D(\mathbf{R}^{+};E)$ with $E$ being a general Tychonoff space. The methods herein are also used in companion papers to establish the: (3) existence of, uniqueness of and convergence to martingale problem solutions, (4) classical Fujisaki-Kallianpur-Kunita and Duncan-Mortensen-Zakai filtering equations and stationary filters, (5) finite-dimensional convergence to stationary signal-filter pairs, (6) invariant measures of Markov processes, and (7) Ray-Knight theory all in general settings.
复制及其在弱收敛中的应用
本文提出了一种将函数、测度和随机过程复制到紧致度量空间的方法。许多结果很容易为复制对象建立,然后转移回原始对象。本文解决了两个问题来证明该方法:(1)一般拓扑空间上过程的有限维收敛性。(2)给出了Skorokhod空间$D(\mathbf{R}^{+};E)$的紧性和相对紧性判据,其中$E$为一般Tychonoff空间。本文的方法也被用于在其他论文中建立:(3)鞅问题解的存在性、唯一性和收敛性,(4)经典的fujisaki - kallianpurl - kunita和duncan - mortenseni - zakai滤波方程和平稳滤波器,(5)平稳信号-滤波器对的有限维收敛性,(6)马尔可夫过程的不变测度,以及(7)一般情况下的Ray-Knight理论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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