This paper surveys some recent developments in measures of association related to a new
coefficient of correlation introduced by the author. A straightforward extension of this …

Testing independence has garnered increasing attention in the econometric and statistical
literature. Many tests have been proposed, most of which are inconsistent against all …

Test of independence is of fundamental importance in modern data analysis, with broad
applications in variable selection, graphical models, and causal inference. When the data is …

An ideal independence test should possess three properties: it should be zero-
independence equivalent, numerically efficient, and asymptotically normal. We introduce a …

Multivariate responses are commonly encountered in many applications with high-
dimensional input variables. Feature screening has been shown to be a very useful data …

Semi-competing risks data, including probably correlated non-terminal event and terminal
event times, are frequently encountered in medical research. Work on semi-competing risks …

To study the stock market networks, we propose a community detection procedure, Spectral
Clustering On Ratios-of-Eigenvectors with Composite Coefficient of Determination. This …

This paper considers semiparametric sieve estimation in high-dimensional single index
models. The use of Hermite polynomials in approximating the unknown link function …

In chapter 1 we study explained variation under the additive hazards regression model for
right-censored data. We consider different approaches for developing such a measure, and …

Feature screening is a popular and efficient statistical technique in processing ultrahigh-
dimensional data. When a regression model consists both categorical and continuous …