Mary Meyer Professor

Office: Statistics Building 212

Phone: (970) 491-5762


Google Scholar:


  • PhD Statistics, University of Michigan


My main area of research is estimation and inference in statistical models with inequality constraints. This includes non-parametric function estimation using constrained regression splines, density and hazard function estimation with shape constraints, models with order restrictions.


Estimation and inference of domain means subject to qualitative constraints.Cristian Oliva Aviles, Mary C. Meyer, Jean D. Opsomer Survey Methodology.
cgam: An R Package for the Constrained Generalized Additive ModelXiyue Liao, Mary C. Meyer Journal of Statistical Software, 2019.
Checking Validity of Monotone Domain Mean EstimatorsCristian Oliva Aviles, Mary C. Meyer, Jean D. Opsomer Canadian Journal of Statistics, 2, 2019.
Estimation and inference in mixed effect regression models using shape constraints, with application to tree height estimationXiyue Liao, Mary C. Meyer Journal of the Royal Statistical Society, Series C.
Probability and Mathematical Statistics: Theory, Applications, and Practice in RMary C. Meyer SIAM, 2019.
A Formal Method for Detecting and Describing Cultural Complexity: Extending Classical Consensus AnalysisMichael G. Lacy, Jeffrey G. Snodgrass, Mary C. Meyer, HJ Francois Dengah, Noah Benedict Field Methods, 3, 2018.
A Framework for Estimation and Inference in Generalized Additive Models with Shape and Order RestrictionsMary C. Meyer STATISTICAL SCIENCE, 4, 2018.
Convergence rates for constrained regression splinesMary C. Meyer, Soo-Young Kim, Haonan Wang JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2018.
Constrained Partial Linear Regression SplinesMary C. Meyer Statistica Sinica, 2018.
Change-point estimation using shape-restricted regression splinesXiyue Liao, Mary C. Meyer JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2017.