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001			279047
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007			cr nn 008mamaa
008			150903s2008 xxu| o |||| 0|eng d
020			_a9780387746760 _99780387746760
024	7		_a10.1007/9780387746760 _2doi
035			_avtls000332527
039		9	_a201509030230 _bVLOAD _c201404122154 _dVLOAD _c201404091925 _dVLOAD _y201402041031 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aHD30.23
100	1		_aDrew, John H. _eautor _9303137
245	1	0	_aComputational Probability : _bAlgorithms and Applications in the Mathematical Sciences / _cby John H. Drew, Diane L. Evans, Andrew G. Glen, Lawrence M. Leemis.
264		1	_aBoston, MA : _bSpringer US, _c2008.
300			_brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aIn Operations Research & Management Science, _x0884-8289 ; _v117
500			_aSpringer eBooks
505	0		_aComputational Probability -- Maple for APPL -- Algorithms for Continuous Random Variables -- Data Structures and Simple Algorithms -- Transformations of Random Variables -- Products of Random Variables -- Algorithms for Discrete Random Variables -- Data Structures and Simple Algorithms -- Sums of Independent Random Variables -- Order Statistics -- Applications -- Reliability and Survival Analysis -- Stochastic Simulation -- Other Applications.
520			_aComputational probability encompasses data structures and algorithms that have emerged over the past decade that allow researchers and students to focus on a new class of stochastic problems. COMPUTATIONAL PROBABILITY is the first book that examines and presents these computational methods in a systematic manner. The techniques described here address problems that require exact probability calculations, many of which have been considered intractable in the past. The first chapter introduces computational probability analysis, followed by a chapter on the Maple computer algebra system. The third chapter begins the description of APPL, the probability modeling language created by the authors. The book ends with three applications-based chapters that emphasize applications in survival analysis and stochastic simulation. The algorithmic material associated with continuous random variables is presented separately from the material for discrete random variables. Four sample algorithms, which are implemented in APPL, are presented in detail: transformations of continuous random variables, products of independent continuous random variables, sums of independent discrete random variables, and order statistics drawn from discrete populations. The APPL computational modeling language gives the field of probability a strong software resource to use for non-trivial problems and is available at no cost from the authors. APPL is currently being used in applications as wide-ranging as electric power revenue forecasting, analyzing cortical spike trains, and studying the supersonic expansion of hydrogen molecules. Requests for the software have come from fields as diverse as market research, pathology, neurophysiology, statistics, engineering, psychology, physics, medicine, and chemistry.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aEvans, Diane L. _eautor _9303138
700	1		_aGlen, Andrew G. _eautor _9303139
700	1		_aLeemis, Lawrence M. _eautor _9303140
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387746753
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-74676-0 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c279047 _d279047