Abstract
This chapter presents several probabilistic representation methods of the random nature of input parameters for structural models. The concept of the random field and its discretization are discussed with graphical interpretations. In later sections, we discuss linear regression and polynomial regression procedures which can be applied to stochastic approximation. A procedure for checking the adequacy of a regression model is also given with a representative example of the regression problem.
Keywords
- Probability Density Function
- Cumulative Distribution Function
- Random Field
- Covariance Function
- Orthogonal Polynomial
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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2.4 References
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(2007). Preliminaries. In: Reliability-based Structural Design. Springer, London . https://doi.org/10.1007/978-1-84628-445-8_2
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DOI: https://doi.org/10.1007/978-1-84628-445-8_2
Publisher Name: Springer, London
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