Jeremy Gaskins, PhD
|Bioinformatics and Biostatistics
Ph.D. (2013) Statistics, University of Florida
B.S. (2007) Mathematics and Applied Mathematics, Auburn University
I joined the Department of Bioinformatics & Biostatistics at UofL in the fall of 2013 at the rank of Assistant Professor.Research Interests
My primary research interests include longitudinal data, missing data models, covariance/correlation estimation, Bayesian methodology, and Markov chain Monte Carlo methods.Teaching
PHST 691 - Bayesian StatisticsPublications: Books
Daniels, M.J., and J.T. Gaskins. (2013) Bayesian methods for the analysis of mixed categorical and continuous (incomplete) data. In Analysis of Mixed Data: Methods and Applications (edited by A.R. de Leon and K. Carriere Chough). pg. 189-208. Chapman & Hall/CRC PressPublications: Journal Articles
Gaskins, J.T., and M.J. Daniels. (2013) A nonparametric prior for simultaneous covariance estimation. Biometrika, 100(1): 111-124.
Gaskins, J.T., and M.J. Daniels. (2013) Sparsity inducing prior distributions for correlation matrices of longitudinal data. Journal of Computational and Graphical Statistics. In press. (Accepted author version available online).