Why Culture Matters: Revisiting the Sino-Indian Border War of 1962

This article examines the nuclear command and control (C²) system implemented in Pakistan since 1998, and discusses its potential consequences for the risk of inadvertent or unauthorised use of nuclear weapons. I argue that troubled civil-military relations and Pakistan's doctrine of ‘asymmetric escalation’ account for the creation of a command and control system with different characteristics during peacetime and military crises. Although the key characteristics of Pakistan's nuclear C² system allow relatively safe nuclear operations during peacetime, operational deployment of nuclear weapons during military standoffs is likely to include only rudimentary protections against inadvertent or unauthorised nuclear release. The implication of this study is that any shift from peacetime to wartime command and control procedures is likely to further destabilise Indo-Pakistani relations during the early stages of a diplomatic or military standoff, and introduce a non-trivial risk of accidental escalation to the nuclear level.     

‘A fly in outer space’: Soviet ballistic missile defence during the Khrushchev period

Although the Soviet missile defence effort was begun to protect the USSR from attack by nuclear missiles, Khrushchev was quick to see its political value, and used the prospect of an anti‐ballistic missile system to emphasize Soviet technological superiority. Within the Soviet armed forces there was widespread consensus about the importance of ABM's damage‐limiting role. The debates about strategy for future war in Soviet military publications demonstrate that support in the armed forces for an ABM capability transcended service loyalties and remained remarkably strong even after 1962, when technical problems and an effort to improve relations with the US following the Cuban Missile Crisis meant that the missile defence project no longer enjoyed the public backing of senior Party and military figures.     

Book reviews

Norman Cigar, Genocide in Bosnia: The Policy of “Ethnic Cleansing”. College Station, Texas: Texas A&M University Press, 1995. Pp.xiv + 247; app., map, notes, cartoon.

Maria Jose Moyano, Argentina's Lost Patrol: Armed Struggle, 1969–1979. New Haven: Connecticut Yale University Press, 1995. Pp.xiii + 226, biblio., abbreviations, 10 figures, 1 map, tables, index; $25/£16.95. ISBN 0–300–01622–6.

Donald E. Schulz and Deborah Sundloff Schulz, The United States, Honduras, and the Crisis in Central America, Westview Thematic Studies in Latin America, Boulder, Co: Westview, 1994. Pp.368, map, figure, select biblio., abbreviations, index. $52.50/£37.50; (cloth) $17.95/£11.95 (paper). ISBN 0–8133–1324–4 and 1323–6.

Joseph H. Alexander and Merrill L. Bartlett, Sea Soldiers in the Cold War: Amphibious Warfare 1945–1991. Annapolis, Maryland: Naval Institute Press, 1995. Pp.iii + 178, 1 map, 29 illus, biblio, index. $32.95. ISBN

Gary P. Cox, The Halt in the Mud: French Strategic Planning from Waterloo to Sedan. Westview Press, 1994. Pp.258, maps, notes, biblio, index. £33.50. ISBN 0–133–1536–0.     

On the effectiveness of top‐down strategy for forecasting autoregressive demands

We investigate the relative effectiveness of top‐down versus bottom‐up strategies for forecasting the demand of an item that belongs to a product family. The demand for each item in the family is assumed to follow a first‐order univariate autoregressive process. Under the top‐down strategy, the aggregate demand is forecasted by using the historical data of the family demand. The demand forecast for the items is then derived by proportional allocation of the aggregate forecast. Under the bottom‐up strategy, the demand forecast for each item is directly obtained by using the historical demand data of the particular item. In both strategies, the forecasting technique used is exponential smoothing. We analytically evaluate the condition under which one forecasting strategy is preferred over the other when the lag‐1 autocorrelation of the demand time series for all the items is identical. We show that when the lag‐1 autocorrelation is smaller than or equal to 1/3, the maximum difference in the performance of the two forecasting strategies is only 1%. However, if the lag‐1 autocorrelation of the demand for at least one of the items is greater than 1/3, then the bottom‐up strategy consistently outperforms the top‐down strategy, irrespective of the items' proportion in the family and the coefficient of correlation between the item demands. A simulation study reveals that the analytical findings hold even when the lag‐1 autocorrelation of the demand processes is not identical. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007.     

Sequential learning versus no learning in Bayesian regression models

We consider two regression models: linear and logistic. The dependent variable is observed periodically and in each period a Bayesian formulation is used to generate updated forecasts of the dependent variable as new data is observed. One would expect that including new data in the Bayesian updates results in improved forecasts over not including the new data. Our findings indicate that this is not always true. We show there exists a subset of the independent variable space that we call the “region of no learning.” If the independent variable values for a given period in the future are in this region, then the forecast does not change with any new data. Moreover, if the independent variable values are in a neighborhood of the region of no learning, then there may be little benefit to wait for the new data and update the forecast. We propose a statistical approach to characterize this neighborhood which we call the “region of little learning.” Our results provide insights into the trade‐offs that exist in situations when the decision maker has an incentive to make an early decision based on an early forecast versus waiting to make a later decision based on an updated forecast. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 532–548, 2014     

A logistic regression/Markov chain model for NCAA basketball

Each year, more than $3 billion is wagered on the NCAA Division 1 men's basketball tournament. Most of that money is wagered in pools where the object is to correctly predict winners of each game, with emphasis on the last four teams remaining (the Final Four). In this paper, we present a combined logistic regression/Markov chain model for predicting the outcome of NCAA tournament games given only basic input data. Over the past 6 years, our model has been significantly more successful than the other common methods such as tournament seedings, the AP and ESPN/USA Today polls, the RPI, and the Sagarin and Massey ratings. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

On the bivariate negative binomial distribution of mitchell and paulson

The bivariate negative binomial distribution of Mitchell and Paulson [17] for the case b = c = 0 is shown to be equivalent to the accident proneness model of Edwards and Gurland [4] and Subrahmaniam [19,20]. The diagonal series expansion of its joint probability function is then derived. Two other formulations of this distribution are also considered: (i) as a mixture model, which showed how it arises as the discrete analogue to the Wicksell-Kibble bivariate gamma distribution, and (ii) as a consequence of the linear birth-and-death process with immigration.     

A reliability model with states of partial operation

This article generalizes the classical dichotomic reliability model to include states of partial operation. The generalized model can be considered as a special case of a general jump process. Both continuous and discrete state spaces are included. The relationship to cumulative damage shock models is discussed. Properties of the model are investigated and these are illustrated via examples. The equivalence of three forms of component independence is proved, but this equivalence does not generalize to the property of zero covariance. Alternative forms of series and parallel connections and the effect of component replacement are discussed.     

An application of empirical bayes techniques to the simultaneous estimation of many probabilities

Consider the following situation: Each of N different combat units is presented with a number of requirements to satisfy, each requirement being classified into one of K mutually exclusive categories. For each unit and each category, an estimate of the probability of that unit satisfying any requirement in that category is desired. The problem can be generally stated as that of estimating N different K-dimensional vectors of probabilities based upon a corresponding set of K-dimensional vectors of sample proportions. An empirical Bayes model is formulated and applied to an example from the Marine Corps Combat Readiness Evaluation System (MCCRES). The EM algorithm provides a convenient method of estimating the prior parameters. The Bayes estimates are compared to the ordinary estimates, i.e., the sample proportions, by means of cross validation, and the Bayes estimates are shown to provide considerable improvement.