Preprints and Publications

Spencer, N. A., and Shalizi, C. R. (2023). Projective, Sparse, and Learnable Latent Position Network Models Annals of Statistics 51 (6) 2506 - 2525, https://doi.org/10.1214/23-AOS2340

Spencer, N. A., & Miller, J. W. (2022). Strong uniform laws of large numbers for bootstrap means and other randomly weighted sums. arXiv preprint arXiv:2209.04083.

Acuna, P., Supnet-Wells, M. L., Spencer, N. A., de Guzman, J. K., Russo, M., Hunt, A., ... & Sharma, N. (2023). Establishing a natural history of X-linked dystonia parkinsonism. Brain Communications, fcad106.

Spencer, N. A., Junker, B. W., & Sweet, T. M. (2022). Faster MCMC for Gaussian latent position network models. Network Science, 10(1), 20-45.

Spencer, N. A., and Murray, J. S. (2020) A Bayesian Hierarchical Model for Evaluating Forensic Footwear Evidence  The Annals of Applied Statistics, Volume 14, Number 3, 1449-1470.

Spencer, N. A., Ranjan, P., and Mendivil, F., (2019) Isomorphism Check for 2^n Factorial Designs with Randomization Restrictions Journal of Statistical Theory and Practice 13 (60).

Barnes*, B., Clark*, J., Kadane*, J., Priestley*, M., Spencer*, N.; Tator*, D., Wauthier*, D., Yohannan*, J (2018), Latent Print Processing of Glassine Stamp Bags Containing Suspected Heroin: The Search for an Efficient and Safe Method Journal of Forensic Identification, 68, pp. 588-611.

Jewell*, S., Spencer*, N., Bouchard-Côté, A. (2015), Atomic Spatial Processes, Proceedings of The 32nd International Conference on Machine Learning, pp. 248–256, 2015.

Ranjan, P. and Spencer, N. (2014), Space-filling Latin Hypercube Designs based on Randomization Restrictions in Factorial Experiments, Statis. & Prob. Letters, 94, 239-247.

Ranjan, P. and Spencer, N. (2013), A Unified Approach to Factorial Designs with Randomization Restrictions In Calcutta Statistical Association Bulletin, Vol. 65 (Special 8th Triennial Symposium Proceedings Volume), Nos. 257-260, pp 43–62.

*equal contributions

I can also be found on Google scholar.