7 papers
Conditional Mean Independence, Global Sensitivity Analysis, and Variable Screening Using nearest neighbor Graphs
Anirban Chatterjee, Ziang Niu, Bhaswar B. Bhattacharya
Quantifying how much of the variation in a response is explained by its conditional mean is central to many statistical problems. In this paper, we develop a unified framework for…
Scaling Limits for Ising Models on Inhomogeneous Random Graphs and Applications
Sanchayan Bhowal, Anirban Chatterjee, Somabha Mukherjee
In this paper, we derive quenched scaling limits for linear functionals and the empirical spin field of Ising models on inhomogeneous random graphs generated by a graphon (encompas…
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.…
Asymptotic Normality of Subgraph Counts in Sparse Inhomogeneous Random Graphs
Sayak Chatterjee, Anirban Chatterjee, Abhinav Chakraborty +1
In this paper, we derive the asymptotic distribution of the number of copies of a fixed graph in a random graph sampled from a sparse graphon model. Specifically, we prov…
A Kernel-Based Conditional Two-Sample Test Using Nearest Neighbors (with Applications to Calibration, Regression Curves, and Simulation-Based Inference)
Anirban Chatterjee, Ziang Niu, Bhaswar B. Bhattacharya
In this paper we introduce a kernel-based measure for detecting differences between two conditional distributions. Using the `kernel trick' and nearest-neighbor graphs, we propose…
Higher-Order Graphon Theory: Fluctuations, Degeneracies, and Inference
Anirban Chatterjee, Soham Dan, Bhaswar B. Bhattacharya
Exchangeable random graphs, which include some of the most widely studied network models, have emerged as the mainstay of statistical network analysis in recent years. Graphons, wh…
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal
The Ising model, originally developed as a spin-glass model for ferromagnetic elements, has gained popularity as a network-based model for capturing dependencies in agents' outputs…