Statistical validation of stochastic models
- Los Alamos National Lab., NM (United States). Engineering Science and Analysis Div.
- Sandia National Labs., Albuquerque, NM (United States). Experimental Structural Dynamics Dept.
- Univ. of Texas, El Paso, TX (United States). Dept. of Civil Engineering
It is common practice in structural dynamics to develop mathematical models for system behavior, and the authors are now capable of developing stochastic models, i.e., models whose parameters are random variables. Such models have random characteristics that are meant to simulate the randomness in characteristics of experimentally observed systems. This paper suggests a formal statistical procedure for the validation of mathematical models of stochastic systems when data taken during operation of the stochastic system are available. The statistical characteristics of the experimental system are obtained using the bootstrap, a technique for the statistical analysis of non-Gaussian data. The authors propose a procedure to determine whether or not a mathematical model is an acceptable model of a stochastic system with regard to user-specified measures of system behavior. A numerical example is presented to demonstrate the application of the technique.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States); Department of Defense, Washington, DC (United States); Texas Univ., Austin, TX (United States)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 432964
- Report Number(s):
- SAND--96-2610C; CONF-970233--5; ON: DE97000663; CNN: Contract F49620951051B
- Country of Publication:
- United States
- Language:
- English
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