Book reviews

Third World Military Expenditure: Determinants and Implications. By Robert McKinlay. Frances Pinter, London (1989)

The UK Defence Industrial Base: Development and Future Policy Options. By Trevor Taylor and Keith Hayward. Brassey's, London, for Royal United Services Institute (1989), ISBN 0-08-036713-5, £22.50

Mutiny. By Lawrence James. Buchan & Enright, London (1987), ISBN 0-907675-70-0, £12.95; Scapegoat! Famous Courts Martial. By John Harris. Severn House, London (1988), ISBN 0-7278-2103-2, £12.95; In Glass Houses. By Robert Boyes. Military Provost Staff Corps Association, Colchester (1986), ISBN 0-9513467-0-9, £6.50 (paperback)

The Nuclear Weapons World: Who, How and Where. Edited by Patrick Burke. Frances Pinter, London (1988), ISBN 086187-705-5, £50.00

Merchants of Treason—America's Secrets for Sale. By Thomas B. Allen and Norman Polmar. Robert Hale, London (1988), ISBN 0-7090-3543-8, £14.95 ($21.95); Intelligence and Intelligence Policy in a Democratic Society. Edited by Stephen J. Cimbala. Transnational Publishers, Dobbs Ferry, NY (1987), ISBN 0-941320-44-8, $37.50; Catching Spies—Principles and Practices of Counterespionage. By H. H. A. Cooper and Lawrence J. Redlinger. Paladin Press, Boulder, CO (1988), ISBN 0-87364-466-2, $24.95

The BattleshipRoyal Sovereignand Her Sister Ships. By Peter C. Smith. William Kimber, Wellingborough (1988), ISBN 0-7183-0704-6, £12.95; Air Power at Sea, 1945 to Today. By John Winton. Sidgwick & Jackson, London (1987), £9.95     

The effect of nonnormality on variables sampling plans

Acceptance sampling plans based on variables have been in use for many years. Recently, there has been a renewal of interest in these plans, because of the relative efficiencies that they offer with respect to attributes sampling regarding sample size. Furthermore, in situations where acceptable quality levels are very small, and a high level of protection is desired, variables sampling is often much more efficient than attributes sampling. An important disadvantage of variables sampling is that the distribution of the parameter being inspected must be known. Most standard variables sampling plans assume that the distribution of this parameter is normal. This article examines the effect of the normality assumption in variables sampling. Methods to detect departures from normality are reviewed.     

Aggregating assignment constraints

This article shows how simple systems of linear equations with {0,1} variables can be aggregated into a single linear equation whose {0,1} solutions are identical to the solutions of the original system. Structures of the original systems are exploited to keep the aggregator's integer coefficients from becoming unnecessarily large. The results have potential application in integer programming and information theory, especially for problems that contain assignment-type constraints along with other constraints. Several unresolved questions of a number-theoretic nature are mentioned at the conclusion of the article.     

On a large sample test for the traffic intensity in GI|G|s queue

A large sample test based on normal approximation for the traffic intensity parameter ρ in the cases of single and multiple-server queues has been proposed. The test procedure is developed without imposing steady-state assumptions and is applicable to queueing systems with general interarrival and service-time distributions.     

A Lanchester-type model of combat with stochastic rates

The effects of environmental stochasticity in a Lanchester-type model of combat are investigated. The methodology is based on a study of stochastic differential equations with random parameters characterized by dichotomous Markov processes. Exact expressions for the Laplace transforms of the time evolution of the first- and second-order moments of the system are obtained. A special case when the fluctuations in the parameters occur with great rapidity in comparison with the natural time scale of the system is also analyzed. The stochastic stability in the mean-square sense is discussed by using the Routh–Hurwitz criterion and it is found that the stochastic perturbations tend to destabilize the system.     

An analysis of constrained robust regression estimators

Multicollinearity and nonnormal errors are problems often encountered in the application of linear regression. Estimators are proposed for dealing with the simultaneous occurrence of both multicollinearity and nonnormality. These estimators are developed by combining biased estimation techniques with certain robust criteria. An iteratively reweighted least-squares procedure is used to compute the estimates. The performance of the combined estimators is studied empirically through Monte Carlo experiments structured according to factorial designs. With respect to a mean-squared-error criterion, the combined estimators are superior to ordinary least-squares, pure biased estimators, and pure robust estimators when multicollinearity and nonnormality are present. The loss in efficiency for the combined estimators relative to least squares is small when these problems do not occur. Some guidelines for the use of these combined estimators are given.