Analysis of high-dimensional data has led to increased interest in both
...
In high-dimensional generalized linear models, it is crucial to identify...
For many tasks of data analysis, we may only have the information of the...
Sparse reduced rank regression is an essential statistical learning meth...
The expanding number of assets offers more opportunities for investors b...
Non-Euclidean data is currently prevalent in many fields, necessitating ...
The paper proposes a time-varying parameter global vector autoregressive...
Background: Travel restrictions as a means of intervention in the COVID-...
We introduce a new library named abess that implements a unified framewo...
Distribution function is essential in statistical inference, and connect...
Best group subset selection aims to choose a small part of non-overlappi...
Microsatellite instability (MSI) is associated with several tumor types ...
Retina image processing is one of the crucial and popular topics of medi...
The pandemic of COVID-19 has caused severe public health consequences ar...
Reduced rank regression is popularly used for modeling the relationship ...
The rapid development of modern technology facilitates the appearance of...
In this paper, we extend a measure of divergence between two distributio...
We introduce a new R package, BeSS, for solving the best subset selectio...