Nuclear Crisis Outcomes: Winning, Uncertainty, and the Nuclear Balance
Abstract
The binomial distribution is widely used across many different disciplines. In cases where data can be represented with a binomial distribution, an estimate for the binomial distribution parameter (for the probability of success) is often produced. However, uncertainty surrounding this estimate is only sometimes reported, in part due to the opacity of the various methods available for determining this uncertainty. Failing to appropriately analyze uncertainty can lead to erroneous, or at least incomplete, conclusions. Here, we explore both Bayesian and frequentist methods for quantifying uncertainty in the binomial distribution parameter, and discuss each method's various advantages and limitations. Our work is motivated by nuclear crisis outcome data. While nuclear crises have been studied to determine the likelihood of the nuclear-superior, compared to the nuclear-inferior, state winning in a crisis, there is great uncertainty present in these estimates for the probability of winning. We demonstrate methods that appropriately quantify such uncertainty and use nuclear crisis outcome data to illustrate applications of the methods we present, as well as to demonstrate insights that can be provided by explicitly analyzing uncertainty.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2019
- Accession Number
- AD1075531
Entities
People
- James Scouras
- Kelly Rooker
Organizations
- Johns Hopkins University Applied Physics Laboratory