Skip to content

DAE

Seminar

Enhancing Stochastic Kriging Metamodels with Stochastic Gradient Estimators

Nelson, B; Ankenman, B (Northwestern University)
Wednesday 07 September 2011, 11:30-12:00

Seminar Room 1, Newton Institute

Abstract

Stochastic kriging is the natural extension of kriging metamodels for the design and analysis of computer experiments to the design and analysis of stochastic simulation experiments where response variance may differ substantially across the design space. In addition to estimating the mean response, it is sometimes possible to obtain an unbiased or consistent estimator of the response-surface gradient from the same simulation runs. However, like the response itself, the gradient estimator is noisy. In this talk we present methodology for incorporating gradient estimators into response surface prediction via stochastic kriging, evaluate its effectiveness in improving prediction, and specifically consider two gradient estimators: the score function/likelihood ratio method and infinitesimal perturbation analysis.

Presentation

[pdf ]

Video

The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.

Back to top ∧