Markov chain sampling has recently received considerable attention in particular in the context of Bayesian computation and maximum likelihood estimation. This paper discusses the use of Markov chain splitting, originally developed for the theoretical analysis of general state space Markov chains, to introduce regeneration into Markov chain samplers. This allows the use of regenerative methods ...

This is an expository paper, focussing on the following scenario. We have two Markov chains, M and M. By some means, we have obtained a bound on the mixing time of M. We wish to compare M with M in order to derive a corresponding bound on the mixing time of M. We investigate the application of the comparison method of Diaconis and Saloff-Coste to this scenario, giving a number of theorems which...

Markov chain Monte Carlo is an umbrella term for algorithms that use Markov chains to sample from a given probability distribution. This paper is a brief examination of Markov chain Monte Carlo and its usage. We begin by discussing Markov chains and the ergodicity, convergence, and reversibility thereof before proceeding to a short overview of Markov chain Monte Carlo and the use of mixing time...

This paper gives a brief introduction to Markov Chain Monte Carlo methods, which offer a general framework for calculating difficult integrals. We start with the basic theory of Markov chains and build up to a theorem that characterizes convergent chains. We then discuss the MetropolisHastings algorithm.

We consider a financial market driven by a continuous time homogeneous Markov chain. Conditions for absence of arbitrage and for completeness are spelled out, non-arbitrage pricing of derivatives is discussed, and details are worked out for some cases. Closed form expressions are obtained for interest rate derivatives. Computations typically amount to solving a set of first order partial differ...

The problem of delay-range-dependent exponential synchronization is investigated for Lur’e master-slave systems with delay feedback control and Markovian switching. Using LyapunovKrasovskii functional and nonsingular M-matrix method, novel delayrange-dependent exponential synchronization in mean square criterions are established. The systems discussed in this paper is advanced system, and takes...

There are a lot of intensive researches on handwritten character recognition (HCR) for almost past four decades. The research has been done on some of popular scripts such as Roman, Arabic, Chinese and Indian. In this paper we present a review on HCR work on the four popular scripts. We have summarized most of the published paper from 2005 to recent and also analyzed the various methods in crea...

In this article, we summariseMonte Carlo simulationmethods commonly used in Bayesian statistical computing. We give descriptions for each algorithm and provide R codes for their implementation via a simple 2-dimensional example. We compare the relative merits of these methods qualitatively by considering their general user-friendliness, and numerically in terms of mean squared error and computa...

We study a stochastic model of electricity production and consumption where appliances are adaptive and adjust their consumption to the available production, by delaying their demand and possibly using batteries. The model incorporates production volatility due to renewables, ramp-up and rampdown time, uncertainty about actual demand versus planned production, delayed and evaporated demand due ...

I show how to run an N-time-step Markov chain simulation in a circular fashion, so that the state at time 0 follows the state at time N ?1 in the same way as states at times t follow those at times t?1 for 0 < t < N. This wrap-around of the chain is achieved using a coupling procedure, and produces states that all have close to the equilibrium distribution of the Markov chain, under the assumpt...