Curtis B. Storlie

Winkel, M. A., Stallrich, J. W., Storlie, C. B., & Reich, B. J. (2021). Sequential Optimization in Locally Important Dimensions. TECHNOMETRICS, 63(2), 236–248. https://doi.org/10.1080/00401706.2020.1714738

Reich, B. J., Kalendra, E., Storlie, C. B., Bondell, H. D., & Fuentes, M. (2012). Variable selection for high dimensional Bayesian density estimation: application to human exposure simulation. Journal of the Royal Statistical Society. Series C, Applied Statistics, 61, 47–66.

Storlie, C. B., Bondell, H. D., Reich, B. J., & Zhang, H. H. (2011). Surface estimation, variable selection, and the nonparametric oracle property. Statistica Sinica, 21(2), 679–705.

Storlie, C. B., Bondell, H. D., & Reich, B. J. (2010). A Locally Adaptive Penalty for Estimation of Functions With Varying Roughness. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 19(3), 569–589. https://doi.org/10.1198/jcgs.2010.09020

Storlie, C. B., & Helton, J. C. (2008). [Review of Multiple predictor smoothing methods for sensitivity analysis: Description of techniques]. Reliability Engineering & System Safety, 93(1), 28–54.

Storlie, C. B., & Helton, J. C. (2008). Multiple predictor smoothing methods for sensitivity analysis: Example results. RELIABILITY ENGINEERING & SYSTEM SAFETY, 93(1), 55–77. https://doi.org/10.1016/j.ress.2006.10.013

Helton, J. C., Johnson, J. D., Oberkampf, W. L., & Storlie, C. B. (2007). A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 196(37-40), 3980–3998. https://doi.org/10.1016/j.cma.2006.10.049