000			02000nam a2200349 i 4500
005			20250919184854.0
008			130819s2012 enka b 001 0 eng
020			_a9780470744536 (hbk.) _cRM330.66
039		9	_a201312231302 _bzabidah _c201312171226 _dros _y08-19-2013 _zros
040			_aDLC _beng _cDLC _erda _dDLC _dUKM
090			_aQA279.5.R557
090			_aQA279.5 _b.R557
100	1		_aRios Insua, David, _d1964-
245	1	0	_aBayesian analysis of stochastic process models / _cDavid Rios Insua, Fabrizio Ruggeri, Michael P. Wiper.
264		1	_aChichester, West Sussex : _bWiley, _c2012.
300			_axiii, 290 p. : _bill. ; _c24 cm
504			_aIncludes bibliographical references and index.
520			_a'This book provides analysis of stochastic processes from a Bayesian perspective with coverage of the main classes of stochastic processing, including modeling, computational, inference, prediction, decision-making and important applied models based on stochastic processes. In offers an introduction of MCMC and other statistical computing machinery that have pushed forward advances in Bayesian methodology. Addressing the growing interest for Bayesian analysis of more complex models, based on stochastic processes, this book aims to unite scattered information into one comprehensive and reliable volume'-- _cProvided by publisher.
520			_a'A unique book on Bayesian analyses of stochastic process based models'-- _cProvided by publisher.
650		0	_aBayesian statistical decision theory.
650		0	_aStochastic processes.
700	1		_aRuggeri, Fabrizio.
700	1		_aWiper, Michael P.
907			_a.b15704464 _b2019-11-12 _c2019-11-12
942			_c01 _n0 _kQA279.5.R557
914			_avtls003537472
990			_aza
991			_aFakulti Sains dan Teknologi
998			_at _b2013-06-08 _cm _da _feng _genk _y0 _z.b15704464
999			_c682030 _d682030