With reference to a general class of empirical-type likelihoods, we develop higher-order asymptotics for the frequentist coverage of Bayesian credible sets based on posterior quantiles and highest posterior density. These asymptotics, in turn, characterise members of the class that allow...

We consider a very general class of empirical discrepancy statistics that includes the Cressie--Read discrepancy statistics and, in particular, the empirical likelihood ratio statistic. Higher-order asymptotics for expected lengths of associated confidence intervals are investigated. An explicit...

In this paper we provide rather weak conditions on a distribution which would guarantee that the t-statistic of a random vector of order n follows the t-distribution with n-1 degrees of freedom. The results sharpen the earlier conclusions of Mauldon [Characterizing properties of statistical...

In this paper, the Bayesian local influence approach is employed to diagnose the adequacy of the growth curve model with Rao's simple covariance structure, based on the Kullback-Leibler divergence. The Bayesian Hessian matrices of the model are investigated in detail under an abstract...

This note provides a theoretical justification for the optimal foldover plans for two-level designs, including the regular 2s-p, non-regular, saturated and supersaturated designs.

In this paper we propose a new method, based on the conditional distribution method in Monte-Carlo methods, to generate the uniform distribution on the domain Tn(a,b)={(x1,...,xn): 0[less-than-or-equals, slant]ai[less-than-or-equals, slant]xi[less-than-or-equals, slant]bi[less-than-or-equals,...

Riccomagno et al. [1997. Lattice-based D-optimum design for Fourier regression. Ann. Statist. 25, 2313-2317] gave a comprehensive study on D-optimality under a symmetric Fourier regression model and gave a characterization on orthogonality, complete orthogonality and D-optimality of lattice...

For the growth curve model with an unstructured covariance matrix, the posterior distributions of the dispersion matrix is derived under a non-informative prior distribution. The results are especially useful for Bayesian inference as well as Bayesian diagnostics of the model.

Uniform designs have been used in computer experiments (Fang et al., Technometrics 42 (2000) 237). A uniform design seeks its design points to be uniformly scattered on the experimental domain. When the number of runs is large, to search a related uniform design is a NP hard problem. Therefore,...