[演講公告] 12/23 統研所專題演講(二)

[missergirl (貓貓)]

交通大學、清華大學 統計學研究所 專題演講

題　目：Model uncertainty and validation

主講人：Dr. William M. Briggs (Various companies & Cornell University, USA )

時　間：99年12月23日(星期四)上午11:10-12:00
        (上午10:50-11:10茶會於交大統計所429室舉行)

地　點：交大綜合一館427室



Abstract

Models that pass quality checks using traditional measures of goodness of fit
might not appear as impressive when examined predictively. Ordinary model
diagnostics and quantifications of uncertainties miss aspects of performance
that are most important to the model user.  The first thing we'll do is
define what it means to say a model makes a prediction, and then emphasize
the importance of predictive inference.  Calibration will be explained.
 Bayesian p-values and their competitors, predictive scores, will be
contrasted.  Since what makes a model good or bad is how useful it is, skill
scores become necessary.  Examples of commonly-used models will be given.



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