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Bayesian Inference for High Dimensional Changing Linear Regression with Application to Minnesota House Price Index Data
Abhirup Datta, Hui Zou, Sudipto Banerjee
In many applications, the dataset under investigation exhibits heterogeneous regimes that are more appropriately modeled using piece-wise linear models for each of the data segment…
CoCoLasso for High-dimensional Error-in-variables Regression
Abhirup Datta, Hui Zou
Much theoretical and applied work has been devoted to high-dimensional regression with clean data. However, we often face corrupted data in many applications where missing data and…
SURE Information Criteria for Large Covariance Matrix Estimation and Their Asymptotic Properties
Danning Li, Hui Zou
Consider independent and identically distributed -dimensional Gaussian random vectors with covariance matrix The problem of estimating when is much larger than…
Regularized rank-based estimation of high-dimensional nonparanormal graphical models
Lingzhou Xue, Hui Zou
A sparse precision matrix can be directly translated into a sparse Gaussian graphical model under the assumption that the data follow a joint normal distribution. This neat propert…
Strong oracle optimality of folded concave penalized estimation
Jianqing Fan, Lingzhou Xue, Hui Zou
Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usual…
Nonconcave penalized composite conditional likelihood estimation of sparse Ising models
Lingzhou Xue, Hui Zou, Tianxi Cai
The Ising model is a useful tool for studying complex interactions within a system. The estimation of such a model, however, is rather challenging, especially in the presence of hi…