English

Replication and Its Application to Weak Convergence

Probability 2020-11-03 v1

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(R+;E)D(\mathbf{R}^{+};E) with EE 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.

Keywords

Cite

@article{arxiv.2011.00484,
  title  = {Replication and Its Application to Weak Convergence},
  author = {Chi Dong and Michael A. Kouritzin},
  journal= {arXiv preprint arXiv:2011.00484},
  year   = {2020}
}

Comments

203 pages, 5 figures