In an FCFS queueing system, the response time R is defined as the time spent by a customer from arrival
until departure; R also can be viewed as the time elapsed from the instant of job arrival until its completion.
The mean response time E(R) is an important index for a customer to determine whether entering the FCFS
queueing system. Hence E(R) plays a significant role in system performance measures for an FCFS queueing
system.
The statistical inference in queueing problems are rarely found in the literature and the work of related
problems in the past mainly concentrates on only parametric statistical inference, in which the distribution
of population is with a known form (except perhaps for the parameters). The pioneering paper in parameter
estimation problem was first proposed by Clarke [1], who developed maximum likelihood estimates for the
arrival and service parameters of an M/M/1 queue. Lilliefors [2] examined the confidence intervals for the
M/M/1, M/Ek/1 and M/M/2 queues. For a G/G/1 queue, Basawa and Prabhu [3] studied moment estimatesular Parzen–Rosenblatt kernel estimator of f