000			03359cam a2200409 i 4500
999			_c532059 _d532059
001			17435073
003			NUST
005			20191107114842.0
008			120820t20122013flua b 001 0 eng
010			_a 2012025210
020			_a9781439872062 (hardback)
020			_a1439872066 (hardback)
038			_aMSOHAIL
040			_aDLC _beng _cDLC _erda _dDLC
042			_apcc
050	0	0	_aQA273 _b.R8528 2013
082	0	0	_a519.2 _223
084			_aMAT029010 _aTEC029000 _2bisacsh
100	1		_aRotarʹ, V. I. _q(Vladimir Ilʹich), _eauthor. _925350
245	1	0	_aProbability and stochastic modeling / _cVladimir I. Rotar.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c[2012]
264		4	_c©2013
300			_axvii, 490 pages : _billustrations ; _c27 cm
336			_atext _2rdacontent
337			_aunmediated _2rdamedia
338			_avolume _2rdacarrier
504			_aIncludes bibliographical references (pages 471-474) and index.
520			_a"Preface: This book is intended as a first course in probability with an emphasis on stochastic modeling. Distinctive features of the book concern its contents and format as well. The Contents. The exposition is rigorous; with rare exceptions, all assertions are proven; almost every topic found in a traditional introductory probability course is covered. On the other hand, the book pays substantial attention to stochastic modeling, which is atypical for first-course textbooks on Probability. Cases in point are Markov chains, birth-death processes (including queuing processes), reliability models, and other topics, both theoretical and applied. We also consider a number of concrete models (for example, a model of financial markets, or the principal components scheme); sometimes, even with real world data. The goal here is not to teach particular models or numerical methods but rather help the student to better appreciate general concepts and theoretical results, and demonstrate practical possibilities and restrictions of different approaches under consideration. The same concerns examples and exercises with use of Excel. Besides the traditional material, we also pay attention to topics usually skipped (or almost skipped) in introductory courses, though in the author's opinion, they are becoming increasingly important. In particular, this concerns martingales, classification of dependency structures, and risk evaluation. The format of the book. The material is presented in the form of two nested "routes". Route 1 contains the basic material designed for a one semester course. This material is self-contained and has a moderate level of difficulty. Route 2 contains all of Route 1, offers a more complete exposition, and is suited for a two-semester course or self-study"-- _cProvided by publisher.
650		0	_aProbabilities _vTextbooks. _9112
650		0	_aStochastic models _vTextbooks. _910955
650		7	_aMATHEMATICS / Probability & Statistics / Bayesian Analysis. _2bisacsh _925351
650		7	_aTECHNOLOGY & ENGINEERING / Operations Research. _2bisacsh _925352
856	4	2	_3Cover image _uhttp://jacketsearch.tandf.co.uk/common/jackets/covers/websmall/978143987/9781439872062.jpg
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK