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

Students

CV

Teaching: STATS 401: Applied Statistical Methods II. MATH/STATS 425: Introduction to Probability. STATS 531: Analysis of Time Series. STATS 631: Modeling and Analysis of Time Series Data. STATS 620: Applied Probability and Stochastic Modeling. STATS 700: Topics in Applied Statistics: Phylodynamic Inference. STATS 810: Literature Proseminar.

Software: The Pypomp library for Python with JAX. The pomp R package. The panelPomp R package. The spatPomp R package.

Research topics: Time series analysis with applications including ecology, epidemiology and health economics. Methodological work on inference for partially observed stochastic dynamic systems.

Selected publications:

Wheeler, J., Rosengart, A. L., Jiang, Z., Tan, K., Treutle, N. and Ionides, E. L. (2024). Informing policy via dynamic models: Cholera in Haiti. PLOS Computational Biology 20 e1012032. doi. arxiv. github.

Ning, N. and Ionides, E. L. (2023). Iterated block particle filter for high-dimensional parameter learning: Beating the curse of dimensionality. Journal of Machine Learning Research 24(82) 1-76. pdf. arxiv. github.

Breto, C., Ionides, E. L., and King, A. A. (2019). Panel data analysis via mechanistic models. Journal of the American Statistical Association 115 1178-1188. doi. arxiv. github.

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 112 719-724. 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.

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. supporting text.