Non-analogue Monte Carlo methods are useful when the direct simulation techniques are insufficient. To use the additional discretization, Monte Carlo estimates are biased and it is desirable to optimize the connection between discretization parameters and the sample size. In this connection, the book investigates variances of non-analogue Monte Carlo estimates, uniform minimization of variances by choosing a computational model and the minimization of computational cost of non-analogue Monte Carlo methods. This book is essentially new with respect to previous monographs on the Monte Carlo methods. Contents:Non-Analogue Monte Carlo Methods (NAMCM)Minimax NAMCMEffective NAMCM in Transfer TheorySolving Boundary Problems for Elliptic EquationsCost of Global Monte Carlo Methods Readership: Applied mathematicians, computational mathematicians, physicists and engineers. keywords:Minimization of Computational Costs;Non-Analogue Monte Carlo Methods;Integral Equations;Transfer Theory;Elliptic EquationsIt provides (see Section 1.2) conditions for the standard estimates (to be considered henceforth) of the Monte Carlo method for ... For this paper, the a#39; collisiona#39; estimate is more suitable as it has been shown in Chapter 2 that this estimate isanbsp;...

Title | : | Minimization of Computational Costs of Non-Analogue Monte Carlo Methods |

Author | : | G A Mikhailov |

Publisher | : | - 1992-01-10 |

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