The paper studies large sample asymptotic properties of the Maximum Likelihood Estimator (MLE) for the parameter of a continuous time Markov chain, observed in white noise. Using the method of weak convergence of likelihoods due to I.Ibragimov and R.Khasminskii [14], consistency, asymptotic normality and convergence of moments are established for MLE under certain strong ergodicity conditions o...

This infinite-dimensional object is a function of the current state. We have to decide how to approximate it numerically. One approach is to discretize the state and approximate the conditional expectation by the finite set of its values at each point in the state space. This technique involves replacing the continuous-valued Markov chain for λ with a finitely-many-discrete-valued Markov chain....

State-space models are a very general class of time series capable of modeling-dependent observations in a natural and interpretable way. We consider here the case where the latent process is modeled by a Markov chain taking its values in a continuous space and the observation at each point admits a distribution dependent of both the current state of the Markov chain and the past observation. I...

To estimate the premium an investor should expect from extended hedge fund lockups, Derman et al. (2009) proposed a three-state discrete-time Markov Chain to model the state of a hedge fund, allowing the state to change randomly among the states “good,” “sick” and “dead” every year. The lockup premium measures the consequence of being stuck with a sick fund. To be more realistic, we propose an ...

Motivated by applications in Markov chain Monte Carlo, we discuss what it means for one Markov chain to be an approximation to another. Specifically included in that discussion are situations in which a Markov chain with continuous state space is approximated by one with finite state space. A simple sufficient condition for close approximation is derived, which indicates the existence of three ...

In this paper, we obtain the Rényi entropy rate for irreducible-aperiodic Markov chains with countable state space, using the theory of countable nonnegative matrices. We also obtain the bound for the rate of Rényi entropy of an irreducible Markov chain. Finally, we show that the bound for the Rényi entropy rate is the Shannon entropy rate.

In this paper, absorbing Markov chain models are developed to determine the optimum process mean levels for both a single-stage and a serial two-stage production system in which items are inspected for conformity with their specification limits. When the value of the quality characteristic of an item falls below a lower limit, the item is scrapped. If it falls above an upper limit, the item is ...

This paper presents the analysis of a renewal input  finite buffer queue wherein the customers can decide either to  join the queue with a probability or balk. The service process is Markovian service process ($MSP$) governed  by an underlying $m$-state Markov chain. Employing the supplementary  variable and imbedded Markov chain techniques,   the steady-state system length distributions at pre...