Supersaturated designs (SSDs) can save considerable cost in industrial experimentation when many potential factors are introduced in preliminary studies. Analyzing data in SSDs is challenging because the number of experiments is less than the number of candidate factors. In this paper, we...

Evaluation of reproducibility is important in assessing whether a new method or instrument can reproduce the results from a traditional gold standard approach. In this paper, we propose a measure to assess measurement agreement for functional data which are frequently encountered in medical...

In this paper we are concerned with Bayesian statistical inference for a class of elliptical distributions with parameters[mu]and[Sigma]. Under a noninformative prior distribution, we obtain the posterior distribution, posterior mean, and generalized maximim likelihood estimators...

Local polynomial regression is a useful non-parametric regression tool to explore fine data structures and has been widely used in practice. We propose a new non-parametric regression technique called "local composite quantile regression smoothing" to improve local polynomial regression further....