Publications

Machine Learning Models Identify Inhibitors of New Delhi Metallo-β-lactamase (NDM)

Published in Journal of Chemical Information and Modeling, 2024

Cheng, Z, Aitha, M., Thomas, C., Sturgill, A., Fairweather, M., Hu, A., Bethel, C. Rivera, D., Dranchak, P., Thomas, P., Li, H., Feng, Q., Tao, K., Song, M., Sun, N., Wang, S., Silwal, S.B., Page, R., Fast, W., Bonomo, R., Weese, M.L., Martinez, Waldyn G., Inglese, J., Crowder, M. (2024) " Machine Learning Models Identify Inhibitors of New Delhi Metallo-β-lactamase (NDM)" Accepted: Journal of Chemical Information and Modeling

A Graphical Comparison of Screening Designs using Support Recovery Probabilities

Published in Journal of Quality Technology, 2024

Young. H.K., Weese, M.L., Stallrich, J.W., Smucker, B.J., Edwards, D.J.. (2024) " A Graphical Comparison of Screening Designs using Support Recovery Probabilities." Accepted: Journal of Quality Technology.

Robustness of the One-Class Peeling method to the Gaussian Kernel Bandwidth

Published in Quality and Reliability Engineering International, 2022

Lee, L., Weese, M.L., Martinez, W.G., and Jones-Farmer, L.A. "Robustness of the One-Class Peeling method to the Gaussian Kernel Bandwidth." : Quality and Reliability Engineering International 38(3) 1289-1301.

Self-Validated Ensemble Models for Design of Experiments

Published in Chemometrics and Intelligent Laboratory Systems, 2021

Lemkus, T., Gotwalt, C., Ramsey, P.R., Weese, M.L., "Self-Validated Ensemble Models for Design of Experiments." Chemometrics and Intelligent Laboratory Systems. 219, 104439

Response Surface Methods: To Reduce or Not to Reduce?

Published in Journal of Quality Technology, 2021

Smucker, B.J., Edwards, D.J, Weese, M.L. "Response surface models: to reduce or not to reduce?." Journal of Quality Technology 53(2), 197-216.

Strategies for Supersatruated Screening: Group Orthogonal and Var(s+) Designs

Published in Technometrics, 2020

Weese, M.L., Stallrich, J.W., Smucker, B.J., Edwards, D.J, "Strategies for Supersatruated Screening: Group Orthogonal and Var(s+) Designs." Technometrics.

A one-class peeling method for multivariate outlier detection with applications in Phase I SPC

Published in Quality and Reliability Engineering International, 2020

Martinez, W.G., Weese, M.L., Jones-Farmer, L.A. (2020). "A one-class peeling method for multivariate outlier detection with applications in Phase I SPC." Quality and Reliabity Engineering International. 36:1272-1295.

Analyzing Definitive Screening Designs: Screening vs. Prediction

Published in Applied Stochastic Models in Business and Industry, 2017

Weese, M.L., Montgomery, D.J., Ramsey,P.J. (2017). "Analyzing Definitive Screening Designs: Screening vs. Prediction." Applied Stochastic Models in Business and Industry. 34(2):244-255.

Criteria for Constructing Powerful Supersaturated Designs when Effect Directions are Known

Published in Journal of Quality Technology, 2017

Weese, M.L., Edwards, D.J., Smucker, B.J.(2017). "A Criteria for Constructing Powerful Supersaturated Designs when Effect Directions are Known." Journal of Quality Technology. 49(3):265-277.

Response Surface Experiments: A meta Analysis

Published in Chemometrics and Intelligent Laboratory Systems, 2017

Ockuly, R., A., Weese, M.L., Smucker, B.J., Edwards, D.J., Chang, L. (2017). "Response Surface Experiments: A meta Analysis." Chemometrics and Intelligent Laboratory Systems. 164:64-75.

Compositional Models and Organizational Research: Application of a Mixture Model to Nonexperimental Data in the Context of CEO Pay

Published in Organizational Reserach Methods, 2017

Campbell, J.T., Weese, M.L. (2017). "Compositional Models and Organizational Research: Application of a Mixture Model to Nonexperimental Data in the Context of CEO Pay." Organizational Research Methods. 20(1):95-120.

Maria Weese