. For implementation the Bayesian and likelihood procedures would perhaps require the same numerical computations, while the … Bayesian literature, with many variations and some preference for two versions labelled pppost and pcpred. The bootstrap method … also directly addresses this Studentization process. We use recent likelihood theory that gives a third order factorization …

. For implementation the Bayesian and likelihood procedures would perhaps require the same numerical computations, while the … Bayesian literature, with many variations and some preference for two versions labelled pppost and pcpred. The bootstrap method … also directly addresses this Studentization process. We use recent likelihood theory that gives a third order factorization …

theoreticians that Bayesian methods were absurd—not merely misguided but obviously wrong in principle. We consider several examples …, beginning with Feller's classic text on probability theory and continuing with more recent cases such as the perceived Bayesian … about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal. …

An elementary sketch of some issues in statistical inference and in particular of the central role of likelihood is …

averages and are smooth functions of a parameter theta. This includes log likelihood, quasi-log likelihood, and least squares …-strong, and strong identification. We determine the asymptotic size (in a uniform sense) of standard t and quasi-likelihood ratio …

averages and are smooth functions of a parameter theta. This includes log likelihood, quasi-log likelihood, and least squares …-strong, and strong identification. We determine the asymptotic size (in a uniform sense) of standard t and quasi-likelihood ratio …