Modelling map positional error to infer true feature location

The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model‐based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber‐sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.     

Carrying American Ideas to the Unconverted : la tentative manquée du MIT d'exporter la recherche opérationnelle au sein de l'OTAN

Recent scholarship on the 'Americanization' of economic and cultural practices emphasize that the Europeans were not passive victims of this 'colonizing' project but selectively appropriated or even completely rejected aspects of it. This paper extends these insights to a scientific field. It describes the failed attempt to export to NATO a theory-based, computer-dependent model of operations research which embedded civilian scientists deeply in the military decision-making process. This conception of operations research and its related social practices was blocked by the British, who rejected a model of operations research which called for a training in advanced mathematics and computing, and who insisted that NATO maintain a strict civil/military divide. 'Americanization' was a negotiated and contested project which, while stimulating an awareness for change in Europe, did not necessarily determine its trajectory.     

Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

A subjectivist approach to consecutive conflict

An easily applied approach is developed to provide one participant in a sequence of conflicts with an optimal strategy. A goal of this article is to demonstrate that it is mathematically feasible to incorporate a decision maker's subjective distributions over the effects his actions will have on the outcomes of future conflicts. Unlike many other approaches, the model of this article does not restrict the beliefs that the participant is allowed to express. The participant, not the decision theorist, decides on what is relevent. Model assumptions required for updating rules, such as Bayesian updating, are not required unless they really are appropriate for the situation.Thanks are due to J. B. Kadane for suggesting the problem and for many helpful discussions.     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

A sea change on the island continent: frameworks for risk assessment,prevention and intervention in child health in Australia

This article overviews prevention and early intervention approaches focusing specifically on their relevance to the health of children and young people in Australia. Australian public health has a sound track record although concealed within the aggregate profile are a number of sub-populations with poorer health indicators. Recognition of this has increased efforts to improve the health of children and young people especially in exploring the impact of social environments within the communities where children are raised. This paper examines emerging research in this area drawing out key lessons and learning from Australian experience in the field of early intervention and prevention in community settings.     

Using a computer simulation game to teach family time use concepts

A computer simulation game designed to give students insights into family time use concepts has been used in an introductory family resource management class at Ohio State University and other universities. The game allows for planning for time use changes over the family life cycle. The game can give students insights into economic and sociological models of time use. It is possible that future versions of the game could be used in family counseling.His research interests include derivation of optimal decision-making rules for families and family financial management.Her research interests include financial management over the life course including financial ratios, baby boomers, and retirement. She received her Ph.D. in 1993 from The Ohio State University in Family Resource Management.His research interests include the time trade-offs made between couples, financial planning over the life cycle, and the interaction of time and money between families and their home-based businesses. He received his Ph.D. in 1993 from The Ohio State University in Family Resource Management.