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.
- Peña Hidalgo, J. I. and Stewart, J. R. Model selection for network data based on spectral information, Applied Network Science, 9 (36) (2024). [PDF]
- 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, 102 (2024), 102375.
- Stewart, J. R. On the time to identify the nodes in a random graph, Statistics & Probability Letters, 195 (2023), 109779. [PDF]
- 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]
- 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]
- 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]
- 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]
- 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
- Stewart, J. R. Consistency of empirical distributions of sequences of graph statistics in networks with dependent edges, (2024+), under review. [Preprint]
- Stewart, J. R. Rates of convergence and normal approximations for estimators of local dependence random graph models, (2024+), under review. [Preprint]
- Li, J. and Stewart, J. R. Learning cross-layer dependence structure in multilayer networks, (2024+), under review. [Preprint]
- 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]