Jonathan Stewart, Ph.D.

Jonathan Stewart, Ph.D.

Research

My research focuses on developing new statistical methods and theory for dependent data with complex structures. My primary focus to-date has been in the field of statistical network analysis, where I have developed novel methodology and theory for high-dimensional statistical models of network data with dependent edges. I am working on new projects and research directions in profile monitoring and change-point detection in dynamical applications in medicine and biology.

Published papers and papers in press

Students are underlined.

  1. Ducharme, L. J., Fujimoto, K., Kuo, J., Stewart, J. R., Taylor, B. and Schneider, J. Collaboration and growth in a large research cooperative: a network analytic approach, Evaluation and Program Planning, (2023+), in press.
  2. Stewart, J. R. On the time to identify the nodes in a random graph, Statistics & Probability Letters, 195 (2023), 109779. [PDF]
  3. Babkin, S., Stewart, J. R., Long, X., and Schweinberger, M. Large-scale estimation of random graph models with local dependence, Computational Statistics and Data Analysis, 152 (2020), 107029. [PDF]
  4. Schweinberger, M., Krivitsky, P., Butts, C., T., and Stewart, J. R. Exponential-family models of random graphs: Inference in finite-, super-, and infinite-population scenarios, Statistical Science, 35 (4) (2020), 627-662. [PDF]
  5. Schweinberger, M. and Stewart, J. Concentration and consistency results for canonical and curved exponential-family models of random graphs, The Annals of Statistics, 48 (2020), 374-396. [PDF]
  6. Stewart, J., Schweinberger, M., Morris, M., and Bojanowski, M. Multilevel network data facilitate statistical inference for curved ergms with geometrically weighted terms, Social Networks, 59 (2019), 98-119. [PDF]
  7. Campbell, I. M., Stewart, J. R., James, R. A., Lupski, J. R., Stankiewicz, P., Olofsson, P., and Shaw, C. A. Parent of origin, mosaicism, and recurrence risk: Probabilistic modeling explains the broken symmetry of transmission genetics, The American Journal of Human Genetics, 95 (4) (2014), 345-359. [PDF]

Papers under review

  1. Stewart, J. R. Consistency of empirical distributions of sequences of graph statistics in networks with dependent edges, (2024+), under review. [Preprint]
  2. Stewart, J. R. Rates of convergence and normal approximations for estimators of local dependence random graph models, (2024+), under review. [Preprint]
  3. Jiaheng, L. and Stewart, J. R. Learning cross-layer dependence structure in multilayer networks, (2024+), under review. [Preprint]
  4. Hidalgo, J. P. and Stewart, J. R. Model selection for network data based on spectral information, (2024+), under review. [Preprint]
  5. Stewart, J. R. and Schweinberger, M. Pseudo-likelihood-based M-estimation of random graphs with dependent edges and parameter vectors of increasing dimension, (2024+), under reivew. [Preprint]