Finite-State Markov-Chain Approximations: A Hidden Markov Approach
有限状态马尔可夫链近似:一种隐马尔可夫方法
This paper proposes a novel finite-state Markov chain approximation method for Markov processes with continuous support, providing both an optimal grid and a transition probability matrix. The method can be used for multivariate processes and processes with time-varying components. It is based on minimizing the information loss between a Hidden Markov Model and the true data-generating process. We provide sufficient conditions under which this information loss can be made…