Development of r,T hybrid sampling plans for exponential lifetime distributions

SUMMARY In the original hybrid reliability acceptance sampling plan RASP developed by Epstein for the exponential lifetime distribution, the sample size n and the number of failures r to be observed are determined given the truncation time T . However, these plans cannot be used when test items are expensive and or limited in number. Therefore, one wishes to have a plan in which n is given. In this paper, we develop hybrid RASPs in which r and T are determined, given n. These plans are tabulated for various combinations of parameter values, so that one may easily determine an appropriate plan.     

Posterior consistency for the spectral density of non-Gaussian stationary time series

Various nonparametric approaches for Bayesian spectral density estimation of stationary time series have been suggested in the literature, mostly based on the Whittle likelihood approximation. A generalization of this approximation involving a nonparametric correction of a parametric likelihood has been proposed in the literature with a proof of posterior consistency for spectral density estimation in combination with the Bernstein–Dirichlet process prior for Gaussian time series. In this article, we will extend the posterior consistency result to non-Gaussian time series by employing a general consistency theorem for dependent data and misspecified models. As a special case, posterior consistency for the spectral density under the Whittle likelihood is also extended to non-Gaussian time series. Small sample properties of this approach are illustrated with several examples of non-Gaussian time series.