June 23, 1999

Charles J. Geyer
Associate Professor
School of Statistics
University of Minnesota
270A Vincent Hall
206 Church St. S. E.
Minneapolis, MN 55455
(612) 625-8511
charlie@stat.umn.edu

Degrees:

• BS 1972 (physics), Hampden-Sydney College.
• MS 1988 (statistics), PhD 1990 (statistics), University of Washington.

Academic Experience:

• University of Washington, Department of Statistics. Teaching Assistant, Research Assistant, and Instructor, 1986-1990.
• University of Chicago, Department of Statistics. NSF Postdoctoral Fellow, 1990-1991.
• University of Minnesota, School of Statistics. Assistant Professor, 1990-1995. Associate Professor, since 1995.

Thesis Advisor: Elizabeth A. Thompson

Publications:

• Geyer, C. J. and Thompson, E. A. (1988). Gene survival in the Asian wild horse (Equus przewalskii): I. Dependence of gene survival in the Calgary breeding group pedigree. Zoo Biology, 7, 313-327.
• Geyer, C. J., Thompson, E. A. and Ryder, O. A. (1989). Gene survival in the Asian wild horse (Equus przewalskii): II. Gene survival in the whole population, in subgroups, and through history. Zoo Biology 8, 313-329.
• Geyer, C. J. (1991). Constrained maximum likelihood exemplified by isotonic convex logistic regression. J. Amer. Statist. Assoc., 86, 717-724.
• Geyer, C. J. and Thompson, E. A. (1992). Constrained Monte Carlo maximum likelihood for dependent data, (with discussion). J. Roy. Statist. Soc. Ser. B, 54 657-699.
• Lin, D. Y. and Geyer C. J. (1992). Computational methods for semiparametric linear regression with censored data. J. Comput. Graph. Statist., 1 77-90.
• Geyer, C. J. (1992). Practical Markov chain Monte Carlo (with discussion). Statist. Sci., 7 473-511.
• Geyer, C. J. (1993). Discussion on the meeting on the Gibbs Sampler and other Monte Carlo methods. J. Roy. Statist. Soc. Ser. B, 55 74-75.
• Geyer, C. J., Ryder, O. A., Chemnick, L. G. and Thompson, E. A. (1993). Analysis of relatedness in the California condors: from DNA fingerprints. Molecular Biology and Evolution, 10 571-589.
• Geyer, C. J. (1994). On the convergence of Monte Carlo maximum likelihood calculations. J. Roy. Statist. Soc. Ser. B, 56 261-274.
• Newton, M. A. and Geyer, C. J. (1994). Bootstrap recycling: A Monte Carlo algorithm for the nested bootstrap. J. Amer. Statist. Assoc., 89 905-912.
• Gentleman, R. and Geyer, C. J. (1994). Maximum likelihood for interval-censored data: Computation and consistency. Biometrika, 81 618-623.
• Geyer, C. J. and Møller, J. (1994). Simulation and likelihood inference for spatial point processes. Scand. J. Statist., 21 359-373.
• Geyer, C. J. (1994). On the Asymptotics of Constrained M-Estimation. Ann. Statist., 22 1993-2010.
• Chan, K. S. and Geyer, C. J. (1994). Discussion of the paper by Tierney. Ann. Statist., 22 1747-1758.
• Geyer, C. J. (1995). Conditioning in Markov chain Monte Carlo. J. Comput. Graph. Statist., 4 2031-2050.
• Geyer, C. J. and Thompson, E. A. (1995). Annealing Markov chain Monte Carlo with applications to ancestral inference. J. Amer. Statist. Assoc., 90 909-920.
• Geyer, C. J. (1995). Discussion of the paper ``Bayesian Computation and Stochastic Systems'' by Julian Besag, Peter Green, David Higdon and Kerrie Mengersen. Statist. Sci., 10 46-48.
• Geyer, C. J. and Tierney, L. (1995). On the convergence of Monte Carlo approximations to the posterior density. In Bayesian Statistics and Econometrics: Essays in Honor of Arnold Zellner, eds. D. Berry, K. M. Chaloner, and J. K. Geweke, New York: Wiley, 389-396.
• Geyer, C. J. (1995). Estimation and Optimization of Functions. In Markov Chain Monte Carlo in Practice, eds. W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, London: Chapman and Hall, 241-258.
• Valberg, S. J., Geyer, C., Sorum, S. A., and Cardinet, G. H., III. (1996). Familial Incidence of Exertional Rhabdomyolysis in Quarter Horse-related breeds. American Journal of Veterinary Research 57 286-290.
• Shaw, F. H. and Geyer, C. J. (1997). Estimation and testing in constrained covariance component models. Biometrika 84 95-102.
• Meeden, G., Geyer, C., Lang, J. and Funo, E. (1998). The admissibility of the maximum likelihood estimator for decomposable log-linear interaction models for contingency tables. Communications in Statistics-Theory and Methods 27 473-494.
• Hobert, J. P. and Geyer, C. J. (1998). Geometric ergodicity of Gibbs and block Gibbs samplers for a hierarchical random effects model. Journal of Multivariate Analysis 67 414-430.
• Geyer, C. J. (1999). Likelihood Inference for Spatial Point Processes. In Stochastic Geometry: Likelihood and Computation, eds. W. Kendall, O. Barndorff-Nielsen and M. N. M. van Lieshout, London: Chapman and Hall/CRC, 141-172.
• Chen, L. S., Geisser, S. and Geyer, C. J. (1999). Monte Carlo Minimization for One-Step Ahead Sequential Control. To appear in Diagnosis and Prediction, IMA Vol. 114.
• Shaw, F., Promislow, D., Tatar, M., Hughes, K. and Geyer, C. Towards reconciling inferences concerning genetic variation in senescence. To appear in Genetics.

Submitted:

• MacLeay, J. M., Valberg, S. J., Geyer, C., Sorum, S., Kassube T., Mickelson, J. R., Santschi, E. M. Genetic evidence for exertional rhabdomyolysis in thoroughbred racehorses. To American Journal of Veterinary Research.

Technical Reports and Conference Proceedings:

• Geyer, C. J. (1988). Software for calculating gene survival and multigene descent probabilities and for pedigree manipulation and drawing. Technical Report 153, Department of Statistics, University of Washington.
• Geyer, C. J. and Thompson, E. A. (1990). Three papers on maximum likelihood in exponential families. Technical Report 188, Department of Statistics, University of Washington.
• Geyer, C. J. (1991). Markov chain Monte Carlo maximum likelihood. Computing Science and Statistics: Proc. 23rd Symp. Interface, 156-163.
• Geyer, C. J. (1991). Estimating Normalizing Constants and Reweighting Mixtures in Markov Chain Monte Carlo. Technical Report No. 568. School of Statistics, University of Minnesota.
• Geyer, C. J. and Thompson, E. A. (1995). A new approach to the joint estimation of relationship from DNA fingerprint data. In Population Management for Survival and Recovery: Analytical Methods and Strategies in Small Population Conservation. eds. J. D. Ballou, M. Gilpin, T. J. Foose, 245-260. New York: Columbia University Press.
• Avise J. C., Haig, S. M., Ryder, O. A., Lynch, M., and Geyer, C. J. (1995). Descriptive genetic studies: applications in population management and conservation biology. In Population Management for Survival and Recovery: Analytical Methods and Strategies in Small Population Conservation. eds. J. D. Ballou, M. Gilpin, T. J. Foose, New York: Columbia University Press, 183-244.
• Mira, A. and Geyer, C. J. (1999). Ordering Monte Carlo Markov Chains. Technical Report No. 632. School of Statistics, University of Minnesota.

 
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