On normal approximation for maximum likelihood estimation from single server queues

This paper is concerned with the rate of convergence of the distribution of the maximum likelihood estimators of the arrival and the service rates in a GI/G/1 queueing system. This revised version was published online in June 2006 with corrections to the Cover Date.     

Large sample inference from single server queues

Problems of large sample estimation and tests for the parameters in a single server queue are discussed. The service time and the interarrivai time densities are assumed to belong to (positive) exponential families. The queueing system is observed over a continuous time interval (0,T] whereT is determined by a suitable stopping rule. The limit distributions of the estimates are obtained in a unified setting, and without imposing the ergodicity condition on the queue length process. Generalized linear models, in particular, log-linear models are considered when several independent queues are observed. The mean service times and the mean interarrival times after appropriate transformations are assumed to satisfy a linear model involving unknown parameters of interest, and known covariates. These models enhance the scope and the usefulness of the standard queueing systems.Partially supported by the U. S. Army Research Office through the Mathematical Sciences Institute of Cornell University.     

Maximum likelihood estimation for noncausal autoregressive processes

We discuss a maximum likelihood procedure for estimating parameters in possibly noncausal autoregressive processes driven by i.i.d. non-Gaussian noise. Under appropriate conditions, estimates of the parameters that are solutions to the likelihood equations exist and are asymptotically normal. The estimation procedure is illustrated with a simulation study for AR(2) processes.     

Duality relations for certain single server queues

In this paper, relations are given between the joint distribution of several variables in a GI/G/1 queue and the joint distribution of variables associated with the busy cycle in the dual queue, that is in the queue which results from the original when the interarrival times and the service times are interchanged. It is assumed that the primal queue has the preemptive-resume last-come-first-served queue discipline while the dual queue may have any queue discipline which is work conserving. These relations generalize a result given recently for M/G/1 and GI/M/1 queues.     

Time-dependent analysis of virtual waiting time behaviour in discrete time queues

Discrete time queueing models have been shown previously to be of practical use for modelling the approximate time-dependent behaviour of queue length in systems of the form M(t)/G/c. In this paper we extend these models to include the time-dependent behaviour of virtual waiting time.     

Optimal design of multi‐server Markovian queues with polynomial waiting and service costs

This paper is concerned with the optimal design of queueing systems. The main decisions in the design of such systems are the number of servers, the appropriate control to have on the arrival rates, and the appropriate service rate these servers should possess. In the formulation of the objective function to this problem, most publications use only linear cost rates. The linear rates, especially for the waiting cost, do not accurately reflect reality. Although there are papers involving nonlinear cost functions, no paper has ever considered using polynomial cost functions of degree higher than two. This is because simple formulas for computing the higher moments are not available in the literature. This paper is an attempt to fill this gap in the literature. Thus, the main contributions of our work are as follows: (i) the derivation of a very simple formula for the higher moments of the waiting time for the M/M/s queueing system, which requires only the knowledge of the expected waiting time; (ii) proving their convexity with respect to the design variables; and (iii) modeling and solving more realistic design problems involving general polynomial cost functions. We also focus on simultaneous optimization of the staffing level, arrival rate and service rate. Copyright © 2013 John Wiley & Sons, Ltd.     

Conditioned limit theorem for virtual waiting time process of the GI/G/1 queue

We prove that in the queueing system GI/G/1 with traffic intensity one, the virtual waiting time process suitably scaled, normed and conditioned by the event that the length of the first busy period exceeds n converges to the Brownian meander process, as n .     

Maximum likelihood estimation in the multi-path change-point problem

Maximum likelihood estimators of the parameters of the distributions before and after the change and the distribution of the time to change in the multi-path change-point problem are derived and shown to be consistent. The maximization of the likelihood can be carried out by using either the EM algorithm or results from mixture distributions. In fact, these two approaches give equivalent algorithms. Simulations to evaluate the performance of the maximum likelihood estimators under practical conditions, and two examples using data on highway fatalities in the United States, and on the health effects of urea formaldehyde foam insulation, are also provided.This work was supported in part by the Natural Science and Engineering Council of Canada, and the Fonds pour la Formation de chercheurs et l'aide à la Recherche Gouvernment du Québec.Lawrence Joseph is also a member of the Department of Epidemiology and Biostatistics of McGill University.     

Maximum likelihood estimation of a multivariate linear functional relationship

Many authors have discussed maximum likelihood estimation in the simple linear functional relationship model. In this paper, we derive maximum likelihood estimators (MLEs) for parameters in a much more general model. Several special cases including the multivariate linear functional relationship model are discussed. Estimators of some of the parameters are shown to be inconsistent.     

Higher moments of the waiting time distribution in M/G/1 retrial queues

This work analyzes the waiting time distribution in the M/G/1 retrial queue. The first two moments of the waiting time distribution are known from the literature. In this work we obtain all the moments of the waiting time distribution.     

Maximum likelihood estimation via duality for cell probabilities subject to convex and log-convex constraints

This article proposes a method for fitting models subject to a convex and log-convex constraint on the probability vector of a product multinomial （binomial） distribution. We present an iterative algorithm for finding the restricted maximum likelihood estimates （MLEs） of the probability vector and show that the algorithm converges to the true solution. Some examples are discussed to illustrate the method.     

Transform-free equations for the stationary waiting time distributions in the queue with poisson arrivals and bulk services

We study a queue with Poisson arrivals and a bulk service rule with two thresholdsN andm on the group sizes. No group of fewer thanN or more thanm customers is served. When the number of available customers is betweenN andm, all customers are served together. The principal results deal with the joint stationary distribution of the waiting time of an arriving customer and of the size of the group in which he is eventually served. After prior computation of the stationary queue length density, the evaluation of the waiting time distribution is reduced to the solution of a system of linear differential equations and a single integral equation. The process describing the waiting time is in general non-Markovian.University of Delaware, Applied Mathematics Institute, Technical Report No. 95 B, May 1984.This research was supported by Grant No. ECS-8205404 of the National Science Foundation and by a Senior U.S. Scientist Award of the Alexander von Humboldt Foundation.     

Approximations for waiting time in GI/G/1 systems

The Sokolov procedure is described and used to obtain an explicit and easily applied approximation for the waiting time distribution in the FIFO GI/G/1 queue.     

Maximum likelihood estimator for the drift of a Brownian flow

The maximum likelihood estimator for the drift of a Brownian flow on ℝ^d, d ⩾ 2, is found with the assumption that the covariance is known. By approximation of the drift with known functions, the statistical model is reduced to a parametric one that is a curved exponential family. The data is the n‐point motion of the Brownian flow throughout the time interval [0, T]. The asymptotic properties of the MLE are also investigated. Copyright © 2000 John Wiley & Sons, Ltd.     

BOOTSTRAP MAXIMUM LIKELIHOOD ESTIMATION OF THE PARAMETER IN SPECTRAL DENSITY OF STATIONARY PROCESSES

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Maximum likelihood estimation from fuzzy data using the EM algorithm

A method is proposed for estimating the parameters in a parametric statistical model when the observations are fuzzy and are assumed to be related to underlying crisp realizations of a random sample. This method is based on maximizing the observed-data likelihood defined as the probability of the fuzzy data. It is shown that the EM algorithm may be used for that purpose, which makes it possible to solve a wide range of statistical problems involving fuzzy data. This approach, called the fuzzy EM (FEM) method, is illustrated using three classical problems: normal mean and variance estimation from a fuzzy sample, multiple linear regression with crisp inputs and fuzzy outputs, and univariate finite normal mixture estimation from fuzzy data.     

Empirical Bayes estimation for queueing systems and networks

Empirical Bayes estimators are derived for standardM/M/1 queues,M/M/1 queues with state-dependent arrival and service rates, finite capacityM/M/1 queues with state-dependent rates and for open Jackson networks. The asymptotic properties of the empirical Bayes estimators are derived both with respect to the conditional distribution of the observations given the parameters, and with respect to the joint distribution of the observations and the parameters.     

An exact FCFS waiting time analysis for a general class of G/G/s queueing systems

A closed form expression for the waiting time distribution under FCFS is derived for the queueing system MGE_k/MGE_m/s, where MGE_n is the class of mixed generalized Erlang probability density functions (pdfs) of ordern, which is a subset of the Coxian pdfs that have rational Laplace transform. Using the calculus of difference equations and based on previous results of the author, it is proved that the waiting time distribution is of the form 1- , under the assumption that the rootsU _j are distinct, i.e. belongs to the Coxian class of distributions of order . The present approach offers qualitative insight by providing exact and asymptotic expressions, generalizes and unifies the well known theories developed for the G/G/1,G/M/s systems and leads to an algorithm, which is polynomial if only one of the parameterss orm varies, and is exponential if both parameters vary. As an example, numerical results for the waiting time distribution of the MGE₂/MGE₂/s queueing system are presented.