Coronavirus disease 2019 (COVID-19) is an infectious caused by severe acute respiratory syndrome coronvirus, which was declared as a global pandemic the World Health Organization on March 11, 2020. In this work, we conduct cross-sectional study to investigate how infection fatality rate (IFR) of COVID-19 may be associated with possible geographical or demographical features infected population....

This work focuses on the issue of variable selection in functional regression. Unlike most work in this framework, our approach does not select isolated points in the definition domain of the predictors, nor does it rely on the expansion of the predictors in a given functional basis. It provides an approach to select full intervals made of consecutive points. This feature improves the interpret...

The dr package for R for dimension reduction regression was first documented in Weisberg (2002). This is a revision of that article, to correspond to version 3.0.0 of dr for R added to CRAN (cran.r-project.org) in Fall 2007. Regression is the study of the dependence of a response variable y on a collection of p predictors collected in x. In dimension reduction regression, we seek to find a few ...

We propose a new variable selection and estimation technique for high dimensional single index models with unknown monotone smooth link function. Among many predictors, typically, only a small fraction of them have significant impact on prediction. In such a situation, more interpretable models with better prediction accuracy can be obtained by variable selection. In this article, we propose a ...

Numerical methods in sparse linear algebra typically rely on a fast and efficient matrix vector product, as this usually is the backbone of iterative algorithms for solving eigenvalue problems or linear systems. Against the background of a large diversity in the characteristics of high performance computer architectures, it is a challenge to derive a cross-platform efficient storage format alon...

An epigenome-wide association study (EWAS) is a large-scale study of human disease-associated epigenetic variation, specifically variation in DNA methylation. High throughput technologies enable simultaneous epigenetic profiling of DNA methylation at hundreds of thousands of CpGs across the genome. The clustering of correlated DNA methylation at CpGs is reportedly similar to that of linkage-dis...

In this elegant paper, F. Yao, Y. Wu, and J. Zou offer a unified treatment of the problem of classifying sparse functional data via sliced inverse regression (e.g., Li, 1991). Such signals are typically encountered in longitudinal studies and various other scientific experiments. In this setting, only a few measurements are available for some, or even all, individuals, and a cumulative slicing ...

Consider estimation of a population mean of a response variable when the observations are missing at random with respect to the covariate. Two common approaches to imputing the missing values are the nonparametric regression weighting method and the Horvitz-Thompson (HT) inverse weighting approach. The regression approach includes the kernel regression imputation and the nearest neighbor imputa...