Charles Geyer

Charles Geyer is a Professor at the School of Statistics, University of Minnesota. His work spans computational statistics, spatial statistics, and statistical genetics, with applications to endangered species conservation and stochastic process modeling.

• Research Interests: Spatial statistics, Markov chain Monte Carlo methods, likelihood inference in exponential families, constrained optimization, and statistical software development.
• Software Contributions: Developed R packages mcmc, aster, rcdd, and trust for Monte Carlo methods, life history analysis, computational geometry, and optimization.
• Teaching: Instructs graduate and undergraduate courses including Stat 5101, Stat 5102, Stat 5421, Stat 5601, and advanced seminars on computational statistics.
• Publications: Notable works include research on maximum likelihood estimation in exponential families, fuzzy P-values, geometric ergodicity in MCMC, and computational methods for conservation genetics.