Search results for "cost of observation"

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Asymptotic optimality of myopic information-based strategies for Bayesian adaptive estimation

2016

This paper presents a general asymptotic theory of sequential Bayesian estimation giving results for the strongest, almost sure convergence. We show that under certain smoothness conditions on the probability model, the greedy information gain maximization algorithm for adaptive Bayesian estimation is asymptotically optimal in the sense that the determinant of the posterior covariance in a certain neighborhood of the true parameter value is asymptotically minimal. Using this result, we also obtain an asymptotic expression for the posterior entropy based on a novel definition of almost sure convergence on "most trials" (meaning that the convergence holds on a fraction of trials that converge…

Statistics and ProbabilityAsymptotic analysisMathematical optimizationPosterior probabilityBayesian probabilityMathematics - Statistics TheoryStatistics Theory (math.ST)050105 experimental psychologydifferential entropyDifferential entropyactive data selection03 medical and health sciences0302 clinical medicineactive learningFOS: Mathematics0501 psychology and cognitive sciencescost of observationdecision theoryMathematicsD-optimalityBayes estimatorSequential estimation05 social sciencesBayesian adaptive estimationAsymptotically optimal algorithmConvergence of random variablesasymptotic optimalitysequential estimation030217 neurology & neurosurgery
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