Abstract Human lifespan increments represent one of the main current risks for governments and pension health benefits providers. Longevity societies imply financial sustainability challenges to guarantee adequate socioeconomic conditions all individuals a longer period. Consequently, modelling population dynamics projecting future longevity scenarios are vital tasks policymakers. As an answer,...

Given a sample from a finite population, we provide a nonparametric Bayesian prediction interval for a finite population mean when a standard normal assumption may be tenuous. We will do so using a Dirichlet process (DP), a nonparametric Bayesian procedure which is currently receiving much attention. An asymptotic Bayesian prediction interval is well known but it does not incorporate all the fe...

The false discovery proportion (FDP) is a useful measure of abundance of false positives when a large number of hypotheses are being tested simultaneously. Methods for controlling the expected value of the FDP, namely the false discovery rate (FDR), have become widely used. It is highly desired to have an accurate prediction interval for the FDP in such applications. Some degree of dependence a...

Resistance spot welding (RSW) includes many variables that can influence the weld properties. The purpose of this study is to develop an analytical model for prediction of thermal history and weld microstructure in RSW and to find the most important process parameters that influence the weld microstructure. A one dimensional model is proposed for prediction about thermal history during cooling ...

Prediction, by interval or point, of an unobserved random variable is a fundamental problem in statistics. This paper deals with constructing a prediction interval on a future observation Xr in an ordered sample of size n from an underlying distribution (under parametric uncertainty), where the first k observations X1 < X2 <  < Xk, 1k<rn, have been observed. Prediction intervals for future...