000			02845nam a2200325 i 4500
008			101228t20122012ne a b 001 0 eng
010			_a2010050137
020			_a9780444515759
020			_a0444515755
035			_a(OCoLC)692291772
040			_aDLC _beng _erda _cDLC _dYDX _dBTCTA _dYDXCP _dBWX _dCDX _dESUDE _dOKN _dKEN
049			_aBAUN_MERKEZ
050	0	4	_aQA298 _b.D86 2012
100	1		_aDunn, William L. _q(William Lee), _d1944-
245	1	0	_aExploring Monte Carlo methods / _cWilliam L. Dunn, J. Kenneth Shultis
264		1	_aAmsterdam ; _aBoston : _bElsevier/Academic Press, _c[2012]
264		4	_c©2012
300			_axvi, 384 pages : _billustrations ; _c24 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index
505	0	0	_t-- Introduction _t-- The Basis of Monte Carlo _t-- Pseudorandom Number Generators _t-- Sampling, Scoring, and Precision _t-- Variance Reduction Techniques _t-- Markov Chain Monte Carlo _t-- Inverse Monte Carlo _t-- Linear Operator Equations _t-- The Fundamentals of Neutral Particle Transport _t-- Monte Carlo Simulation of Neutral Particle Transport _t-- Appendices _t-- Index
520			_aExploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle problem" provides a unifying theme as it is repeatedly used to illustrate many features of Monte Carlo methods. This book provides the basic detail necessary to learn how to apply Monte Carlo methods and thus should be useful as a text book for undergraduate or graduate courses in numerical methods. It is written so that interested readers with only an understanding of calculus and differential equations can learn Monte Carlo on their own. Coverage of topics such as variance reduction, pseudo-random number generation, Markov chain Monte Carlo, inverse Monte Carlo, and linear operator equations will make the book useful even to experienced Monte Carlo practitioners. Provides a concise treatment of generic Monte Carlo methods Proofs for each chapter Appendixes include Certain mathematical functions; Bose Einstein functions, Fermi Dirac functions, Watson functions
650		0	_aMonte Carlo method
700	1		_aShultis, J. Kenneth
900			_a31314
900			_bsatın
942			_2lcc _cKT
999			_c28041 _d28041