Document Type
Conference Paper
Publication Date
2016
Publication Title
Proceedings of the American Society for Engineering Management 2016 International Annual Conference
Pages
1-7 pp.
Conference Name
American Society for Engineering Management International Annual Conference, 26-29 October 2016, Charlotte, North Carolina, USA
Abstract
In the ASEM-IAC 2015, Cotter (2015) proposed a systemic joint deterministic-stochastic dynamic causal Bayesian statistical engineering model that addressed the knowledge gap needed to integrate deterministic mathematical engineering models within a stochastic framework. However, Cotter did not specify the modeling methodology through which statistical engineering models could be developed, diagnosed, and applied to predict systemic mission performance. This paper updates research into the development a hierarchical statistical engineering modeling methodology and sets forth the initial theoretical foundation for the methodology.
Original Publication Citation
Cotter, T. S. (2016). A hierarchical statistical engineering modeling methodology. In In S. Long, E-H. Ng, C. Downing, & B. Nepal (Eds.), Proceedings of the American Society for Engineering Management 2016 International Annual Conference (pp. 1-7). American Society for Engineering Management (ASEM).
Repository Citation
Cotter, Teddy Steven, "A Hierarchical Statistical Engineering Modeling Methodology" (2016). Engineering Management & Systems Engineering Faculty Publications. 135.
https://digitalcommons.odu.edu/emse_fac_pubs/135
Included in
Data Science Commons, Engineering Commons, Mathematics Commons, Statistics and Probability Commons
Comments
Included with the kind permission of the publisher.
Copyright, American Society for Engineering Management, 2016.