000			03995nam a22006255i 4500
001			978-0-387-87837-9
003			DE-He213
005			20181204133149.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387878379 _9978-0-387-87837-9
024	7		_a10.1007/978-0-387-87837-9 _2doi
040			_aISI Library, Kolkata
050		4	_aQA273.A1-274.9
050		4	_aQA274-274.9
072		7	_aPBT _2bicssc
072		7	_aMAT029000 _2bisacsh
072		7	_aPBT _2thema
072		7	_aPBWL _2thema
082	0	4	_a519.2 _223
100	1		_aShonkwiler, Ronald W. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aExplorations in Monte Carlo Methods _h[electronic resource] / _cby Ronald W. Shonkwiler, Franklin Mendivil.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_aXII, 243 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aUndergraduate Texts in Mathematics, _x0172-6056
505	0		_ato Monte Carlo Methods -- Some Probability Distributions and Their Uses -- Markov Chain Monte Carlo -- Optimization by Monte Carlo Methods -- Random Walks.
520			_aMonte Carlo methods are among the most used and useful computational tools available today, providing efficient and practical algorithims to solve a wide range of scientific and engineering problems. Applications covered in this book include optimization, finance, statistical mechanics, birth and death processes, and gambling systems. Explorations in Monte Carlo Methods provides a hands-on approach to learning this subject. Each new idea is carefully motivated by a realistic problem, thus leading from questions to theory via examples and numerical simulations. Programming exercises are integrated throughout the text as the primary vehicle for learning the material. Each chapter ends with a large collection of problems illustrating and directing the material. This book is suitable as a textbook for students of engineering and the sciences, as well as mathematics. The problem-oriented approach makes it ideal for an applied course in basic probability and for a more specialized course in Monte Carlo methods. Topics include probability distributions, counting combinatorial objects, simulated annealing, genetic algorithms, option pricing, gamblers ruin, statistical mechanics, sampling, and random number generation.
650		0	_aDistribution (Probability theory.
650		0	_aComputer science.
650		0	_aAlgorithms.
650		0	_aMathematics.
650		0	_aComputer simulation.
650		0	_aMathematical optimization.
650	1	4	_aProbability Theory and Stochastic Processes. _0http://scigraph.springernature.com/things/product-market-codes/M27004
650	2	4	_aProbability and Statistics in Computer Science. _0http://scigraph.springernature.com/things/product-market-codes/I17036
650	2	4	_aAlgorithms. _0http://scigraph.springernature.com/things/product-market-codes/M14018
650	2	4	_aGame Theory, Economics, Social and Behav. Sciences. _0http://scigraph.springernature.com/things/product-market-codes/M13011
650	2	4	_aSimulation and Modeling. _0http://scigraph.springernature.com/things/product-market-codes/I21025
650	2	4	_aOptimization. _0http://scigraph.springernature.com/things/product-market-codes/M26008
700	1		_aMendivil, Franklin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387879499
776	0	8	_iPrinted edition: _z9780387878362
776	0	8	_iPrinted edition: _z9781489983794
830		0	_aUndergraduate Texts in Mathematics, _x0172-6056
856	4	0	_uhttps://doi.org/10.1007/978-0-387-87837-9
912			_aZDB-2-SMA
942			_cEB
950			_aMathematics and Statistics (Springer-11649)
999			_c426325 _d426325