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math.ST2021
High Dimensional Logistic Regression Under Network Dependence
Somabha Mukherjee, Ziang Niu, Sagnik Halder +2
Logistic regression is key method for modeling the probability of a binary outcome based on a collection of covariates. However, the classical formulation of logistic regression re…
math.ST2021★ 1 cited
Limit theorems for dependent combinatorial data, with applications in statistical inference
Somabha Mukherjee
The Ising model is a celebrated example of a Markov random field, introduced in statistical physics to model ferromagnetism. This is a discrete exponential family with binary outco…
math.ST2021
Efficient Estimation in Tensor Ising Models
Somabha Mukherjee, Jaesung Son, Swarnadip Ghosh +1
The tensor Ising model is a discrete exponential family used for modeling binary data on networks with not just pairwise, but higher-order dependencies. A particularly important cl…