Daniel J Eck
I am an Assistant Professor in the Department of Statistics.
- variance reduction
- robust prediction methods
- maximum likelihood estimation
- exponential family theory
- generalized linear models
I am very interested in developing useful statistical methodology for practitioners in a variety of scientific and industrial fields. I am particularly interested in the tradeoffs between robustness and efficiency in estimation.
I am interested in a wide variety of disciplines within Statistics. These include, but are not limited to, maximum likelihood estimation, exponential family theory, generalized linear models, model averaging, envelope methodology, conformal prediction, causal inference, bootstrap techniques, and multivariate statistics.
UIUC Statistics graduate students are encouraged to reach out to me if you are looking for research opportunities. I currently have several methodological and programming projects in evolutionary biology, variance reduction for estimation of vector-valued parameters, post shock prediction, and baseball.
- PhD Statistics, University of Minnesota, 2017
- BS Mathematics, Southern Illinois University Carbondale, 2009
- STAT 385