A special pattern of consecutive points on a control chart often suggests that the process is out of control due to a special cause. Usually, the probability of such a pattern is not difficult to calculate, but its relation to the rate of a false signal in a control chart is unclear. In this paper we give such a relation for a wide class of patterns that includes six of the eight patterns of special cause discussed in the AT&T Statistical Quality Control Handbook (1958). We derive a surprisingly simple formula for the rate of a false signal in terms of the pattern probability and use this result to improve on the test proposed in the handbook. We also use this formula to give a simple proof of a result of Wolfowitz (1944, Annals of Mathematical Statistics 15: 163–172) and Olmstead (1945, Annals of Mathematical Statistics 17: 24–33) on the monotone sequence. Finally, we give an approximation of the rate of a false signal for another wide class of patterns that covers the two remaining patterns of special cause in the AT&T handbook.

Bidimensional processes defined by dx(t) = ρ(x, y) dt and dy(t) = f(y) dt + σ(y) dW(t), where W(t) is a Wiener process, are considered. Let T(x, y, ξ) = inf[t ≥ 0: x(t] = ξ| x(0) = x, y(0) = y). Explicit expressions for the moment generating function of T(x, y, 0) and for the characteristic function of y(T(x, y, ξ)) are obtained in two special cases. The method of similarity solutions is used. Applications to optimal control problems are presented.

This paper presents diffusion limits for congestion in networks of finite-buffer queues. We consider both loss networks, such as those in communication systems, and networks with manufacturing blocking. In both cases, the number in system process, under conditions of approximate balance under heavy traffic and appropriate scaling of buffers, is shown to behave like a multidimensional Brownian motion reflected to stay within a rectangle in the positive orthant. The two limits differ in directions of reflection off the faces representing full buffers. The limits suggest possible diffusion approximations for finitebuffer networks.

An optimal search among discrete cells for a Markovian object has been labeled the leprechaun problem. This paper discusses the leprechaun's problem: How should the leprechaun behave in order to maximize the probability of being found? A subjective Bayesian approach is taken in modeling the leprechaun.

We analyze service systems where Nservers (N > 2) move one at a time along an array of stations to satisfy a known number of requests for service. Processing a request consists of determining the server to satisfy the request. The cost of processing a request is determined by the distance the server that performs the request has to move. We determine qualitative properties of sequencing strategies that minimize the expected cost incurred by the service of all requests when the array of stations is on a circle or an interval.

It is known that a threshold policy (or trunk reservation policy) is optimal for Erlang's loss system under certain assumptions. This paper examines the robustness of this policy under departures from the standard assumption of Poisson arrivals and shows that the optimal policy has a generalized trunk reservation form.

In this paper, we discuss the late-arrival discrete-time Geom(n)/G(n)/1/N queue with state-dependent arrival and service processes. Whereas the interarrival times are geometrically distributed, service times are conditioned on the system length at the moment of service initiation. The model has wide applications in computer-communications systems, broadband integrated service digital network, asynchronous transfer mode, and so on. The analysis of the model has been carried out, using the supplementary variable technique, and the final results are presented in the form of recursive equations that can be easily implemented on any personal computer. In addition, relations among state probabilities at prearrival, postdeparture, and random epochs have been developed. To demonstrate the effectiveness of our method, some numerical examples have been presented for service-time distributions such as geometric, deterministic, arbitrary, and mixed. The results obtained in this paper should be found useful by system designers who wish to control the congestion by adjusting the service rate if the arrival traffic changes.

We propose a new approach to the analysis of a discrete-time queueing system whose input is generated by a Markov-modulated process and whose service rate is constant. Renewal cycles are identified and the system state on each renewal cycle is modeled as a one-dimensional Markov chain.

We consider Bayes' estimation of the number of independent homogeneous Poisson processes of a superimposed process with unknown rates. The estimation of the total rate of the undetected processes is also considered. Exact posterior distributions are obtained. Monotonicity and asymptotic properties of the Bayes' estimator are also discussed.