Edward Ionides

Edward Ionides
Professor of Statistics
The University of Michigan
1085 South University Ave
Ann Arbor, MI 48109-1107
Phone: 734.615.3332
Fax: 734.763.4676
E-mail: ionides@umich.edu
Office: 453 West Hall

Teaching:
Stat 620: Applied Probability and Stochastic Modeling
Stat 810: Literature Proseminar
Math/Stat 425: Introduction to Probability
Stat 531 / Econ 677: Analysis of Time Series

Research interests:
Time series analysis with applications to ecology, epidemiology, health economics, cell motion and neuroscience. Methodological work on inference for partially observed stochastic dynamic systems.

All publications ; Some tutorials on time series analysis ; Slides for some recent talks ; Curriculum Vitae

Selected publications:
Ionides, E. L., Nguyen, D., Atchade, Y., Stoev, S. and King, A. A. (2015). Inference for dynamic and latent variable models via iterated, perturbed Bayes maps. Proceedings of the National Academy of Sciences of the USA 112 719-724. doi. pdf.

Volz, E. M., Ionides, E., Romero-Severson, E. O., Brandt, M.-G., Mokotoff, E. and Koopman, J. S. (2013). HIV-1 Transmission during Early Infection in Men Who Have Sex with Men: A Phylodynamic Analysis. PLoS Medicine 10 e1001568. doi. pdf.

Ionides, E. L, Bhadra, A., Atchade, Y. and King, A. A. (2011). Iterated filtering. Annals of Statistics 39 1776-1802. doi. pdf. ArXiv.

Bhadra, A., Ionides, E. L., Laneri, K., Pascual, M., Bouma, M. and Dhiman, R. C. (2011). Malaria in Northwest India: Data analysis via partially observed stochastic differential equation models driven by Levy noise. Journal of the American Statistical Association 106 440-451. doi.

Breto, C., He, D., Ionides, E. L. and King, A. A. (2009). Time series analysis via mechanistic models. Annals of Applied Statistics 3 319-348. doi. pdf. ArXiv.

King, A. A., Ionides, E. L., Pascual, M. and Bouma, M. J. (2008). Inapparent infections and cholera dynamics. Nature 454 877-880. doi.

Ionides, E. L., Breto, C. and King, A. A. (2006). Inference for nonlinear dynamical systems. Proceedings of the National Academy of Sciences 103 18438-18443. doi. Supporting online material. pdf and supporting text.