Planning for supply water demands (drinkable and irrigation water demands) is a necessary problem. For this purpose, three subjects must be considered (optimization of water supply systems such as volume of reservoir dams, optimization of released water from reservoir and prediction of next droughts). For optimization of volume of reservoir dams, yield model is applied. Reliability of yield mod...

Summary This article introduces the hug and hop Markov chain Monte Carlo algorithm for estimating expectations with respect to an intractable distribution. The alternates between two kernels, referred as hop. Hug is a nonreversible kernel that repeatedly applies bounce mechanism from recently proposed bouncy particle sampler produce proposal point far current position yet on almost same contour...

A discrete-time conversion is applied to the continuous-time Markov process that describes the dynamics of biochemically reacting systems within the discrete-state stochastic modeling approach (chemical master equation approach). This yields a stochastically identical discrete-time Markov chain and an according formulation of the chemical master equation. Simulating the resulting chain is equiv...

In this paper, we develop approximation methods for solving stochastic control problems. The systems under consideration involve regime switching, modulated by a continuous-time Markov chain. Using Markov chain approximation techniques, we construct discrete-time Markov chains having two components. In addition to convergence of the procedure, numerical experiments and remarks on controlled var...

The present paper investigates the embedding problem for time-homogeneous Markov chains. A discretetime Markov chain with time unit 1 is embeddable in case there exists a compatible Markov chain regarding time unit 1 m (with m ∈ N,m ≥ 2). An embeddable Markov chain has a transition matrix for which there exists an m-th root that is a probability matrix. The present paper examines the embedding ...