129 citations · 141 across the 9 of their papers we have counts for
9 papers
Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model
Ning Wang, Xin Zhang, Qing Mai
The expectation-maximization (EM) algorithm and its variants are widely used in statistics. In high-dimensional mixture linear regression, the model is assumed to be a finite mixtu…
High-dimensional Tensor Response Regression using the t-Distribution
Ning Wang, Xin Zhang, Qing Mai
In recent years, promising statistical modeling approaches to tensor data analysis have been rapidly developed. Traditional multivariate analysis tools, such as multivariate regres…
Envelopes and principal component regression
Xin Zhang, Kai Deng, Qing Mai
Envelope methods offer targeted dimension reduction for various models. The overarching goal is to improve efficiency in multivariate parameter estimation by projecting the data on…
A Doubly-Enhanced EM Algorithm for Model-Based Tensor Clustering
Qing Mai, Xin Zhang, Yuqing Pan +1
Modern scientific studies often collect data sets in the forms of tensors, which call for innovative statistical analysis methods. In particular, there is a pressing need for tenso…
TULIP: A Toolbox for Linear Discriminant Analysis with Penalties
Yuqing Pan, Qing Mai, Xin Zhang
Linear discriminant analysis (LDA) is a powerful tool in building classifiers with easy computation and interpretation. Recent advancements in science technology have led to the po…
Covariate-Adjusted Tensor Classification in High-Dimensions
Yuqing Pan, Qing Mai, Xin Zhang
In contemporary scientific research, it is of great interest to predict a categorical response based on a high-dimensional tensor (i.e. multi-dimensional array) and additional cova…
Model-free Envelope Dimension Selection
Xin Zhang, Qing Mai
An envelope is a targeted dimension reduction subspace for simultaneously achieving dimension reduction and improving parameter estimation efficiency. While many envelope methods h…
The fused Kolmogorov filter: A nonparametric model-free screening method
Qing Mai, Hui Zou
A new model-free screening method called the fused Kolmogorov filter is proposed for high-dimensional data analysis. This new method is fully nonparametric and can work with many t…
Semiparametric Sparse Discriminant Analysis
Qing Mai, Hui Zou
In recent years, a considerable amount of work has been devoted to generalizing linear discriminant analysis to overcome its incompetence for high-dimensional classification (Witte…