6 citations · 10 across the 6 of their papers we have counts for
6 papers
Mean Test with Fewer Observation than Dimension and Ratio Unbiased Estimator for Correlation Matrix
Tiefeng Jiang, Ping Li
Hotelling's T-squared test is a classical tool to test if the normal mean of a multivariate normal distribution is a specified one or the means of two multivariate normal means are…
Tests for High-Dimensional Covariance Matrices Using Random Matrix Projection
Tung-Lung Wu, Ping Li
The classic likelihood ratio test for testing the equality of two covariance matrices breakdowns due to the singularity of the sample covariance matrices when the data dimension $p…
RAPTT: An Exact Two-Sample Test in High Dimensions Using Random Projections
Radhendushka Srivastava, Ping Li, David Ruppert
In high dimensions, the classical Hotelling's test tends to have low power or becomes undefined due to singularity of the sample covariance matrix. In this paper, this proble…
Effect of sampling on the estimation of drift parameter of continuous time AR(1) processes
Radhendushka Srivastava, Ping Li
We study the effect of stochastic sampling on the estimation of the drift parameter of continuous time AR(1) process. A natural distribution free moment estimator is considered for…
High-Dimensional Bayesian Inference in Nonparametric Additive Models
Zuofeng Shang, Ping Li
A fully Bayesian approach is proposed for ultrahigh-dimensional nonparametric additive models in which the number of additive components may be larger than the sample size, though…
Bayesian Ultrahigh-Dimensional Screening Via MCMC
Zuofeng Shang, Ping Li
We explore the theoretical and numerical property of a fully Bayesian model selection method in sparse ultrahigh-dimensional settings, i.e., , where is the number of co…