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20062025
most citedImproved minimax predictive densities under Kullback--Leibler loss

95 citations · 124 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2025

Unified Distributed Estimation Framework for Sufficient Dimension Reduction Based on Conditional Moments

Hongying Li, Minyi Zhu, Yaqi Cao +1

Nowadays, massive datasets are typically dispersed across multiple locations, encountering dual challenges of high dimensionality and huge sample size. Therefore, it is necessary t…

stat.ME2025

Discussion of "Robust Distance Covariance" by S. Leyder, J. Raymaekers, and P.J. Rousseeuw

Hallin Marc, Davide La Vecchia, Hang Liu +1

Distance covariance and distance correlation have long been regarded as natural measures of dependence between two random vectors, and have been used in a variety of situations for…

stat.ME2012★ 20 cited

From Minimax Shrinkage Estimation to Minimax Shrinkage Prediction

Edward I. George, Feng Liang, Xinyi Xu

In a remarkable series of papers beginning in 1956, Charles Stein set the stage for the future development of minimax shrinkage estimators of a multivariate normal mean under quadr…

math.ST2010★ 9 cited

Asymptotic minimax risk of predictive density estimation for non-parametric regression

Xinyi Xu, Feng Liang

We consider the problem of estimating the predictive density of future observations from a non-parametric regression model. The density estimators are evaluated under Kullback--Lei…

math.ST2006★ 95 cited

Improved minimax predictive densities under Kullback--Leibler loss

Edward I. George, Feng Liang, Xinyi Xu

Let and be independent p-dimensional multivariate normal vectors with common unknown mean . Based on only observing , we consi…