Document Type

Conference Paper

Publication Date

2026

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.

Comments

Included with the kind permission of the publisher.

Copyright, American Society for Engineering Management, 2016.

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).

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