Publications and Preprints

P. Sur and E. J. Candès. A modern maximum-likelihood theory for high-dimensional logistic regression. Under revision, Proceedings of the National Academy of Sciences, 2018+. [pdf] [supp] [arXiv]

E. J. Candès and P. Sur. The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression. The Annals of Statistics, to appear, 2018+. [pdf] [arXiv]

P. Sur, Y. Chen, and E. J. Candès. The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled chi-square. Probability Theory and Related Fields, to appear, 2018+. [pdf] [supp] [talk] [arXiv]

P. Sur, G. Shmueli, S. Bose, and P. Dubey. Modeling bimodal discrete data using Conway- Maxwell-Poisson mixture models. Journal of Business and Economic Statistics, Volume 33, 2015 - Issue 3. [pdf] [journal]

S. Bose, G. Shmueli, P. Sur, and P. Dubey. Fitting COM-Poisson mixtures to bimodal count data. Proceedings of the 2013 International Conference on Information, Operations Management and Statistics (ICIOMS 2013), winner of Best Paper Award. [conference]