Background Endometriosis is a condition that significantly affects the quality of life of about
10% of reproductive-aged women. It is characterized by the presence of tissue similar to the …

A reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as
opposed to conventional penalization approaches that use increasing penalties on the …

It is well known that Bridge regression enjoys superior theoretical properties when
compared to traditional LASSO. However, the current latent variable representation of its …

Aims: This research work investigated the best regression technique in handling
multicollinearity using the Ridge, Least Absolute Shrinkage and Selection Operator (LASSO) …

Quantile regression (QR) is an ideal alternative for depicting the conditional quantile
functions of a response variable when the conditions of linear regression are unavailable …

Regularization methods for simultaneous variable selection and coefficient estimation have
been shown to be effective in quantile regression in improving the prediction accuracy. In …

A bridge-randomized penalization that employs a prior for the shrinkage parameter, as
opposed to the conventional bridge penalization with a fixed penalty, often delivers more …

This paper considers a Bayesian approach for joint estimation of the marginal conditional
quantiles from several dependent variables under a linear regression framework. This …

In this paper, we study Bayesian approach for solving large scale linear inverse problems
arising in various scientific and engineering fields. We propose a fused $ L_ {1/2} $ prior …

In real applied fields such as clinical medicine, environmental sciences, psychology as well
as economics, we often encounter the task of conducting statistical inference for longitudinal …