This survey of actuarial credibility theory traces its origins, describes its evolutionary history, gives an account of its main issues and results, and assesses its merits with a view to related work in statistical science. Key-words: Experience rating, limited fluctuation theory, greatest accuracy theory, Bayes, linear Bayes, empirical Bayes, hierarchical models, Hilbert space methods, recurs...

Interest in Bayesian analyses has increased recently, in part as a response to policy makers wanting sound scientific bases for health technology assessments, and associated healthcare funding decisions. This paper provides a brief and simplified description of Bayesian reasoning. Bayes is illustrated in a clinical setting of an expert helping a woman understand the potential risk of passing on...

A new procedure for learning cost-sensitive SVM(CS-SVM) classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the CS-SVM is derived as the minimizer of the associated risk. The extension of the hinge loss draws on recent connections between risk minimization and probability elicitation. These connections are generalized to cost-sensitive classification, in a...

INTRODUCTION Although most risk-stratification scores are derived from preoperative patient variables, there are several intraoperative and postoperative variables that can influence prognosis. Higgins and colleagues previously evaluated the contribution of preoperative, intraoperative and postoperative predictors to the outcome. We developed a Bayes linear model to discriminate morbidity risk ...

In this paper, the well-known proportional hazards model which includes several well-known lifetime distributions such as exponential,Pareto, Lomax, Burr type XII, and so on is considered. With both Bayesian and non-Bayesian approaches , we consider the estimation of parameters of interest based on progressively Type-II right censored samples. The Bayes estimates are obtained based on symmetric...

We investigate the problem of combining the outputs of different translation systems into a minimum Bayes’ risk consensus translation. We explore different risk formulations based on the BLEU score, and provide a dynamic programming decoding algorithm for each of them. In our experiments, these algorithms generated consensus translations with better risk, and more efficiently, than previous pro...

Information-theoretic lower bounds of the Bayes risk have been investigated for a problem parameter estimation in Bayesian setting. Previous studies proven bound different manner and characterized via quantities such as mutual information, Sibson's α-mutual f-divergence, Csiszár's f-informativity. In this paper, we introduce an inequality called “meta-bound risk” show that previous results can ...

in a finite stationary markov chain, transition probabilities may depend on some explanatoryvariables. a similar problem has been considered here. the corresponding posteriors are derived andinferences are done using these posteriors. finally, the procedure is illustrated with a real example.