Probably Almost Bayes Decisions
نویسندگان
چکیده
منابع مشابه
Almost Equalizer, Bayes and Minimax Decision Rules
In this report minimax and near-minimax nonrandomized decision rules under zero-one loss for a restricted location parameter of an absolutely continuous distribution are obtained. Two types of rules are addressed: monotone and non-monotone. A complete-class theorem is obtained in the monotone case, where the results are an extension of a previous work of Zeytinoglu and Mintz (1984) from the cas...
متن کاملGeneralized information criteria for optimal Bayes decisions
This paper deals with Bayesian models given by statistical experiments and standard loss functions. Bayes probability of error and Bayes risk are estimated by means of classical and generalized information criteria applicable to the experiment. The accuracy of the estimation is studied. Among the information criteria studied in the paper is the class of posterior power entropies which includes ...
متن کاملHebbian Learning of Bayes Optimal Decisions
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models for Bayesian decision making typically require datastructures that are hard to implement in neural networks. This article shows that even the simplest and experimentally best supported type of synaptic plasticity, Hebbia...
متن کاملConvex Optimization, Shape Constraints, Compound Decisions, and Empirical Bayes Rules
Estimation of mixture densities for the classical Gaussian compound decision problem and their associated (empirical) Bayes rules is considered from two new perspectives. The first, motivated by Brown and Greenshtein (2009), introduces a nonparametric maximum likelihood estimator of the mixture density subject to a monotonicity constraint on the resulting Bayes rule. The second, motivated by Ji...
متن کاملBayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function
In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information and Computation
سال: 1996
ISSN: 0890-5401
DOI: 10.1006/inco.1996.0074