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Statistical decision theory and bayesian analysis James O. Berger
Publisher: Springer

For an overview of decision theory from this literature (Pearl 2000, ch. Solodovnikov, Introduction to the Statistical Dynamics of Automatic Control Systems, Dover, 1960. Decision Analysis; Decision Support; Risk Analysis and Communication; Statistical Techniques; Information Systems; Collaboration and the Web; Public Sector; Environmental Management; Emergency Management. First, Jim has contributed and is contributing immensely to statistical science from many respects, first and foremost in grounding Bayesian analysis within decision theory. Bayes theorem for updating probabilities; 10.3. Van der Linde, “Bayesian Measures of Model Complexity and Fit,” J. Dr Ben Graham Theory of rough paths. Berger, Statistical Decision Theory and Bayesian Analysis, second ed. Applications to signal processing. Dr David Rossell (from 15 Jul 2013). Professor Gareth Roberts, Stochastic processes, computational statistics, Bayesian statistics and mathematical finance. Note that those from the field of statistics who work on decision theory tend to talk about a "loss function," which is simply an inverse utility function. The basics of probability theory; 10.2. Chen, Approximate Kalman Filtering, World Scientific, 1993. Smith: Bayesian Theory (Wiley, New York, 1994). Berger: Statistical Decision Theory and Bayesian Analysis (Springer, New York, 1985) 2nd ed. Now we return to an analysis of decision scenarios, armed with EDT and the counterfactual formulation of CDT.