14 citations · 33 across the 24 of their papers we have counts for
12 papers · 1 filter
Ising Models on Inhomogeneous Random Graphs: Inference, Local Asymptotic Minimaxity, and Limit of Experiments
Somabha Mukherjee, Sanchayan Bhowal, Anirban Chatterjee +1
In this paper, we develop an inferential framework with sharp asymptotic optimality guarantees for Ising models on inhomogeneous random graphs in the subcritical parameter regime.…
Joint Estimation in Potts Model
Somabha Mukherjee, Sumit Mukherjee, Sayar Karmakar
In this paper, we study estimation of parameters in a two-parameter Potts model with colors and coupling matrix . We characterize concrete sufficient conditions for existe…
Interaction Order Estimation in Tensor Curie-Weiss Models
Somabha Mukherjee
In this paper, we consider the problem of estimating the interaction parameter of a -spin Curie-Weiss model at inverse temperature , given a single observation from this…
Optimal Confidence Bands for Shape-restricted Regression in Multidimensions
Ashley, Datta, Somabha Mukherjee +1
In this paper, we propose and study construction of confidence bands for shape-constrained regression functions when the predictor is multivariate. In particular, we consider the c…
Limit Theorems and Phase Transitions in the Tensor Curie-Weiss Potts Model
Sanchayan Bhowal, Somabha Mukherjee
In this paper, we derive results about the limiting distribution of the empirical magnetization vector and the maximum likelihood (ML) estimates of the natural parameters in the te…
Tensor Recovery in High-Dimensional Ising Models
Tianyu Liu, Somabha Mukherjee, Rahul Biswas
The -tensor Ising model is an exponential family on a -dimensional binary hypercube for modeling dependent binary data, where the sufficient statistic consists of all -fol…
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…
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…
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…
Estimation in Tensor Ising Models
Somabha Mukherjee, Jaesung Son, Bhaswar B. Bhattacharya
The -tensor Ising model is a one-parameter discrete exponential family for modeling dependent binary data, where the sufficient statistic is a multi-linear form of degree $p \ge…
Phase Transitions of the Maximum Likelihood Estimates in the -Spin Curie-Weiss Model
Somabha Mukherjee, Jaesung Son, Bhaswar B. Bhattacharya
In this paper we consider the problem of parameter estimation in the -spin Curie-Weiss model, for . We provide a complete description of the limiting properties of the…
High-dimensional CLT: Improvements, Non-uniform Extensions and Large Deviations
Arun Kumar Kuchibhotla, Somabha Mukherjee, Debapratim Banerjee
Central limit theorems (CLTs) for high-dimensional random vectors with dimension possibly growing with the sample size have received a lot of attention in the recent times. Chernoz…