Maryclare Griffin

Maryclare Griffin

I am a statistician who focuses on problems that arise in the context of regression and problems that arise in the analysis of dependent data. At present, my research includes methods for estimating regression coefficients using relatively little data and prior knowledge about the structure and/or relative magnitudes of the regression coefficients is available, methods for fitting long memory time series models, and methods for fitting Log Gaussian Cox Process models to big datasets. I am especially fond of problems that are computationally challenging, and my work considers both frequentist and Bayesian perspectives.