#high-dimensional inference
4 papers · 1 filter
Bayesian Graphical Models under Positivity Constraints: A Scalable generalized likelihood Approach
Swarnali Raha, Partha Sarkar, Sirani Perera +1
The paper proposes a scalable Bayesian method for estimating precision matrices in Gaussian graphical models with total positivity constraints, using a D‑trace loss and spike‑and‑s…
Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach
Jacob Carlson
The paper proposes a framework that converts unstructured data into sparse, interpretable concept embeddings and then applies high‑dimensional multiple hypothesis testing with sele…
Gaussian Multiplier Bootstrap Procedure for the th Largest Coordinate of High-Dimensional Statistics
Yixi Ding, Qizhai Li, Yuke Shi +2
The paper develops Gaussian multiplier bootstrap techniques for estimating the distribution of the kth largest coordinate (or top‑k order statistics) in high‑dimensional settings,…
High-dimensional inference on jumps in nonparametric time series regression models
Likai Chen, Georg Keilbar, Liangjun Su +1
The paper develops statistical tests for detecting and comparing jumps in the conditional mean of many nonparametric time series, even when the number of series exceeds the sample…