Simulation can be used to estimate a cycle time-throughput (CT-TH) curve of a manufacturing or service system model at several different traffic intensities. Cycle time variance increases rapidly as throughput approaches system capacity; thus, naïve sampling, which expends an equal amount of simulation effort at each traffic intensity being considered, leads to widely differing precision along ...

Abstract: We derive convenient uniform concentration bounds and finite sample multivariate normal approximation results for quadratic forms, then describe some applications involving variance components estimation in linear random-effects models. Random-effects models and variance components estimation are classical topics in statistics, with a corresponding well-established asymptotic theory. ...

Owing to the fact that general semiparametric inference procedures are still underdeveloped for multivariate interval-censored event time data, we propose semiparametric maximum likelihood estimation for the gamma-frailty Cox model under mixed-case interval censoring. We establish the consistency of the semiparametric maximum likelihood estimator (SPMLE) for the model parameters, including the ...

Asymptotics of the variances of many cost measures in random digital search trees are often notoriously messy and involved to obtain. A new approach is proposed to facilitate such an analysis for several shape parameters on random symmetric digital search trees. Our approach starts from a more careful normalization at the level of Poisson generating functions, which then provides an asymptotica...

We study the asymptotic distribution of three-step estimators of a …nite dimensional parameter vector where the second step consists of one or more nonparametric regressions on a regressor that is estimated in the …rst step. The …rst step estimator is either parametric or non-parametric. Using Newey’s (1994) path-derivative method we derive the contribution of the …rst step estimator to the in‡...

This paper gives an asymptotic analysis of the mean-variance (Markowitz-type) portfolio selection under mild assumptions on the market behavior. Theoretical results show the rate of underperformance of the risk aware Markowitz-type portfolio strategy in growth rate compared to the log-optimal portfolio strategy, which does not have explicit risk control. Statements are given with and without fu...

We consider nearly-periodic Markov chains, which may have excellent functional-estimation properties but poor distributional convergence rate. We show how simple modifications of the chain (involving using a random number of iterations) can greatly improve the distributional convergence of the chain. We prove various theoretical results about convergence rates of the modified chains. We also co...