•Incorporates stochastic thresholds to general deterministic systems.•Applies the SIR model of infectious disease to Cyber-Conflict.•Considers the tradeoff between speed of detection and speed of ...vaccination.•Also applied to Lanchester model of Armed Conflict.•Extends differential equation models to a new class of problem.
We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system’s random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations.
The Defense Modeling and Simulation community as been working to improve decisonmaking for the past 75 years. This invited editorial highlights several open problems in our field, which I believe we ...need to collectively make progress against in order to maintain our relevance into the next era.
Inference about time series in weather data can be made in several ways. Current practice focuses on computing summary measures, such as mean and variance, or constructing a reference year from small ...subsets of data derived from multiple years. Some applications require the selection of an instance of observed data over a fixed time frame, typically a year or more, for modeling. In addition, many current methods do not include rainfall as a parameter of interest. This paper reviews and refines existing methods for determining a reference year by creating a metric that measures the (abstract) distance between observed patterns of rainfall. The reference year is then chosen from a group of potential reference years. This method is computationally efficient, easily explained, and robust against differences in the index of reporting, to include leap years. Application of the distance metric to data from Philadelphia, Pennsylvania, and Norfolk, Virginia, shows that it appropriately identifies not only the years that are most typical for a location, but extreme years as well. Both are particularly useful in applications related to urban hydrology, which formed the basis for development of this method. Results also demonstrate that the proposed method is functionally different than existing methods. The distance metric represents an evolutionary step forward, overcomes some difficulties present from other approaches, and would be applicable to a number of cross-disciplinary applications.
Harrison Schramm, Isaac Rubin and Norah Schramm investigate the impact distance learning may have had on the grades of students at a California high school
Harrison Schramm, Isaac Rubin and Norah ...Schramm investigate the impact distance learning may have had on the grades of students at a California high school.
Decisions and investments made today determine the assets and capabilities of the U.S. Navy for decades to come. The nation has many options about how best to equip, organize, supply, maintain, ...train, and employ our naval forces. These decisions involve large sums of money and impact our national security. Navy leadership uses simulation-based campaign analysis to measure risk for these investment options. Campaign simulations, such as the Synthetic Theater Operations Research Model (STORM), are complex models that generate enormous amounts of data. Finding causal threads and consistent trends within campaign analysis is inherently a big data problem. We outline the business and technical approach used to quantify the various investment risks for senior decision makers. Specifically, we present the managerial approach and controls used to generate studies that withstand scrutiny and maintain a strict study timeline. We then describe STORMMiner, a suite of automated postprocessing tools developed to support campaign analysis, and provide illustrative results from a notional STORM training scenario. This new approach has yielded tangible benefits. It substantially reduces the time and cost of campaign analysis studies, reveals insights that were previously difficult for analysts to detect, and improves the testing and vetting of the study. Consequently, the resulting risk assessment and recommendations are more useful to leadership. The managerial approach has also improved cooperation and coordination between the Navy and its analytic partners.
Statistics in pursuit of social justice Schramm, Harrison; Koehlmoos, Tracey Pérez; Nestler, Scott
Significance,
June 2018, 2018-06-01, 20180601, Volume:
15, Issue:
3
Journal Article
Open access
Data skills are in demand. E‐commerce, advertising and artificial intelligence companies are willing to pay substantial sums for statistical knowhow. But statisticians can do more than make their ...mark in business. They can have real impact on people's lives, write Harrison Schramm, Tracey Pérez Koehlmoos and Scott Nestler
Data skills are in demand. E‐commerce, advertising and artificial intelligence companies are willing to pay substantial sums for statistical knowhow. But statisticians can do more than make their mark in business. They can have real impact on people's lives, write Harrison Schramm, Tracey Pérez Koehlmoos and Scott Nestler.
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