000			nam a22 7a 4500
999			_c29318 _d29318
008			190311b xxu||||| |||| 00| 0 eng d
020			_a9781498729604 _c(hbk)
082			_a519.542 _bCOL
100			_aCollazo, Rodrigo A.
245			_aChain event graphs
260			_aBoca Raton : _bCRC Press, _c2018
300			_axx, 233 p. : _bill. ; _c24.2 cm
365			_aGBP _b72.99 _d00
504			_aIncludes bibliographical references.
520			_aA chain event graph (CEG) is an important generalization of the Bayesian Network (BN). BNs have been extremely useful for modeling discrete processes. However, they are not appropriate for all applications. Over the past six years or so, teams of researchers led by Jim Smith have established a strong theoretical underpinning for CEGs. This book systematically and transparently presents the scope and promise of this emerging class of models, together with its underpinning methodology, to a wide audience.
650			_aBayesian statistical decision theory
650			_aMathematical statistics
650			_aGraphic methods
650			_aProbability &​ Statistics
700			_aGörgen, Christiane
700			_aSmith, J. Q.
942			_2ddc _cBK