The Fisher information matrix (FIM) is a critical quantity in several aspects of mathematical modeling, including input selection and confidence region calculation. Analytical determination of the FIM in a general setting, especially in nonlinear models, may be difficult or almost impossible due...

The method of Common Random Numbers is a technique used to reduce the variance of difference estimates in simulation optimization problems. These differences are commonly used to estimate gradients of objective functions as part of the process of determining optimal values for parameters of a...

Consider a Bayesian analysis of a parameter vector, [theta], based on n i.i.d. multivariate measurements. We establish weak convergence of a sequence of parameter values that arises in applying the mean value theorem for integrals to the marginal densities of the sequence of observed vectors. We...

We present four theorems that establish conditions under which the Bayesian posterior distribution is insensitive to the choice of prior distribution. Both finite-sample and asymptotic results are included.