We show fundamental properties of the Markov semigroup recently proposed MCMC algorithms based on Piecewise-deterministic processes (PDMPs) such as Bouncy Particle Sampler, Zig-Zag process or Randomized Hamiltonian Monte Carlo method. Under assumptions typically satisfied in settings, we prove that PDMPs are Feller and their generator admits space infinitely differentiable functions with compac...

In this paper we show that an arbitrary tree-like Markov chain can be embedded in a binary tree-like Markov chain with a special structure. When combined with [7], this implies that any tree structured QBD Markov chain can be reduced to a binary tree-like process. Furthermore, a simple relationship between the V , Rs and Gs matrices of the original and the binary tree-like Markov chain is estab...

INTRODUCTION Andrei Andreyevich Markov was a Russian mathematician born in 1856. Markov's main interests were in number theory, continued fractions, and approximation theory. He studied under P. Chebyshev and worked in the field of probability theory. Markov pioneered work in the area of stochastic processes by creating a model called a Markov chain—a random walk on a state space. His work has ...

the arc costs are assumed to be online parameters of the network and decisions should be made while the costs of arcs are not known. the policies determine the permitted nodes and arcs to traverse and they are generally defined according to the departure nodes of the current policy nodes. in on-line created tours arc costs are not available for decision makers. the on-line traversed nodes are f...

drought is one of the most important weather-induced phenomena which may have severe impacts on different areas such as agriculture, economy, energy production, and society. a number of drought indices have been introduced and used in various countries to date. in the current study, four meteorological drought indices including percent of normal precipitation index (pnpi), standard index of ann...

Bayesian inference often requires the calculation of posterior distributions. Unfortunately, only in special cases (e. g., conjugate priors) it is possible to compute analytically the posterior. Typical approximations to this computation are Laplace approximations and sampling. In sampling-based approaches the integral is approximated numerically. Markov chain Monte Carlo methods (MCMC) can be ...

the aim of this paper is to present the prediction model of the transport energy demand in iran. markov chain grey model (mcgm) is proposed to forecast the transport energy demand of iran. then it is compared with grey model (gm) and regression model. moreover, the mcgm forecasting model is used to forecast the annual gasoline demand of iran up to the year 1400. the aim of this paper is to pres...