Ever since the conception of statistical ranking-and-selection (R8S) problem, a predominant approach has been indifference-zone (IZ) formulation. Under IZ formulation, R8S procedures are designed to provide guarantee on probability correct selection (PCS) whenever performance best system exceeds that second-best by specified amount. We discuss shortcomings this and argue providing good (PGS)—se...

Background: Telomeres are particular sequences of DNA located at the end of the eukaryotic chromosomes that are essential for genome integrity. Telomere length in spermatozoa differs among males, as well as spermatozoa. Also, decreased telomere length in spermatozoa of infertile men is associated with the reduction of fertility potential and embryo quality. Density gradient centrifugation (DGC)...

Background: A significant percent of infertile varicocele patients remained infertile after varicocelectomy and finally most of them refer for assisted reproductive technique (ART) procedures as intra uterine insemination (IUI), in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI). In order to achieve the best results, more strict and accurate standards for ...

In this paper we address the problem of nding the simulated system with the best (maximum or minimum) expected performance when the number of alternatives is nite, but large enough that ranking-and-selection procedures may require too much computation to be practical. Our approach is to use the data provided by the rst stage of sampling in a ranking-and-selection procedure to screen out alterna...

In the problem of selecting a linear model to approximate the true unknown regression model, some necessary and/or sufficient conditions are established for the asymptotic validity of various model selection procedures such as Akaike’s AIC, Mallows’ Cp, Shibata’s FPEλ, Schwarz’ BIC, generalized AIC, crossvalidation, and generalized cross-validation. It is found that these selection procedures c...

Standard assumptions incorporated into Bayesian model selection procedures result in procedures that are not competitive with commonly used penalized likelihood methods. We propose modifications of these methods by imposing nonlocal prior densities on model parameters. We show that the resulting model selection procedures are consistent in linear model settings when the number of possible covar...