In this paper a second degree iterative Monte Carlo method for solving Systems of Linear Algebraic Equations and Matrix Inversion is presented. Comparisons are made with iterative Monte Carlo methods with degree one. It is shown that the mean value of the number of chains N , and the chain length T , required to reach given precision can be reduced. The following estimate on N is obtained N = N...

In this paper we target at developing discretization-invariant, namely dimension-independent, Markov chain Monte Carlo (MCMC) methods to explore PDEconstrained Bayesian inverse problems in infinite dimensional parameter spaces. In particular, we present two frameworks to achieve this goal: Metropolize-then-discretize and discretize-then-Metropolize. The former refers to the method of first prop...

the hydration of biomolecules is vitally important in molecular biology, so in this paper thesolvation energy and radial distribution function of dna bases have been calculated by themonte carlo simulation.the geometries of isolated adenine, guanine, cytosine, and thyminehave been optimized using 6-31+g(d,p) basis function sets. these geometries then will be used inthe monte carlo calculation o...

Background: Monte Carlo (MC) modeling of a linear accelerator is a prerequisite for Monte Carlo dose calculations in external beam radiotherapy. In this study, a simple and efficient model was developed for Elekta SL-25 linear accelerator using MCNP4C Monte Carlo code Materials and methods: The head of Elekta SL-25 linac was simulated for 6 and 18 MV photon beams using MCNP4C MC code. Energ...

Most credit portfolio models currently used by the banking industry rely on Monte Carlo simulations for calculating the probability distribution of the future credit portfolio value, which can be quite computer time consuming. Adding market risk factors, such as stochastic interest rates or credit spreads, as additional ingredients of a credit portfolio model, the computational burden of full M...

We here address the classical bearings-only tracking problem (BOT) for a single object, which belongs to the general class of nonlinear filtering problems. Recently, algorithms based on sequential Monte Carlo methods (particle filtering) have been proposed. As far as performance analysis is concerned, the Posterior Cramér-Rao Bound (PCRB) provides a lower bound on the mean square error. Classic...