We study two Bayesian (Reference Intrinsic and Jeffreys prior), frequentist (MLE PWM) approaches the nonparametric Hill estimator for Pareto related distributions. Three of these are compared in a simulation all four to investigate how much equity risk capital banks subject Basel II banking regulations must hold. The Reference approach, which is invariant under one-to-one transformations data p...

Motivated by the statistical evaluation of complex computer models, we deal with the issue of objective prior specification for the parameters of Gaussian processes. In particular, we derive the Jeffreys-rule, independence Jeffreys and reference priors for this situation, and prove that the resulting posterior distributions are proper under a quite general set of conditions. A proper flat prior...

Large-amplitude oscillatory shear flow (LAOS) is a popular for studying the nonlinear physics of complex fluids. Specifically, the strain rate sweep (also called the strain sweep) is used routinely to identify the onset of nonlinearity. In this paper, we give exact expressions for the nonlinear complex viscosity and the corresponding nonlinear complex normal stress coefficients for the Oldroyd ...

DNA fingerprinting has been hailed by law-enforcement officials as the 20th century’s most important breakthrough in forensic science. They are eager to use the new technology to identify and prosecute violent criminals as well as to exonerate innocent persons who are suspects in criminal cases. Although DNA finger-printing has not yet been adequately tested in the courts, the State Attorney Ge...

This paper studies Bayesian predictive densities based on different priors and frequentist plug-in type predictive densities when the predicted variables are dependent on the observations. Average Kullback-Leibler divergence to the true predictive density is used to measure the performance of different inference procedures. The notion of second-order KL dominance is introduced, and an explicit ...

In Bayesian network structure learning (BNSL), we need the prior probability over structures and parameters. If the former is the uniform distribution, the latter determines the correctness of BNSL. In this paper, we compare BDeu (Bayesian Dirichlet equivalent uniform) and Jeffreys’ prior w.r.t. their consistency. When we seek a parent set U of a variable X , we require regularity that if H(X |...