000			02992nam a22004098i 4500
001			CR9780511617997
003			UkCbUP
005			20200124160223.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			090915s2006||||enk o ||1 0|eng|d
020			_a9780511617997 (ebook)
020			_z9780521863001 (hardback)
020			_z9781107403758 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA274.7 _b.M35 2006
082	0	0	_a519.2/33 _222
100	1		_aMarcus, Michael B., _eauthor.
245	1	0	_aMarkov processes, Gaussian processes, and local times / _cMichael B. Marcus, Jay Rosen.
246	3		_aMarkov Processes, Gaussian Processes, & Local Times
264		1	_aCambridge : _bCambridge University Press, _c2006.
300			_a1 online resource (x, 620 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aCambridge studies in advanced mathematics ; _v100
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aBrownian motion and Ray-Knight theorems -- Markov processes and local times -- Constructing Markov processes -- Basic properties of Gaussian processes -- Continuity and boundedness of Gaussian processes -- Moduli of continuity for Gaussian processes -- Isomorphism theorems -- Sample path properties of local times -- [Rho]-variation -- Most visited sites of symmetric stable processes -- Local times of diffusions -- Associated Gaussian processes.
520			_aThis book was first published in 2006. Written by two of the foremost researchers in the field, this book studies the local times of Markov processes by employing isomorphism theorems that relate them to certain associated Gaussian processes. It builds to this material through self-contained but harmonized 'mini-courses' on the relevant ingredients, which assume only knowledge of measure-theoretic probability. The streamlined selection of topics creates an easy entrance for students and experts in related fields. The book starts by developing the fundamentals of Markov process theory and then of Gaussian process theory, including sample path properties. It then proceeds to more advanced results, bringing the reader to the heart of contemporary research. It presents the remarkable isomorphism theorems of Dynkin and Eisenbaum and then shows how they can be applied to obtain new properties of Markov processes by using well-established techniques in Gaussian process theory. This original, readable book will appeal to both researchers and advanced graduate students.
650		0	_aMarkov processes.
650		0	_aGaussian processes.
650		0	_aLocal times (Stochastic processes)
700	1		_aRosen, Jay, _d1948- _eauthor.
776	0	8	_iPrint version: _z9780521863001
830		0	_aCambridge studies in advanced mathematics ; _v100.
856	4	0	_uhttps://doi.org/10.1017/CBO9780511617997
999			_c516944 _d516942