21 citations · 28 across the 3 of their papers we have counts for
4 papers
Asgl: A Python Package for Penalized Linear and Quantile Regression
Ãlvaro Méndez Civieta, M. Carmen Aguilera-Morillo, Rosa E. Lillo
asgl is an open-source Python package that offers a robust and versatile framework for fitting a variety of regression models including linear, logistic, and, notably, quantile reg…
Fast Partial Quantile Regression
Alvaro Mendez Civieta, M. Carmen Aguilera-Morillo, Rosa E. Lillo
Partial least squares (PLS) is a dimensionality reduction technique used as an alternative to ordinary least squares (OLS) in situations where the data is colinear or high dimensio…
Adaptive sparse group LASSO in quantile regression
Ãlvaro Méndez Civieta, M. Carmen Aguilera-Morillo, Rosa E. Lillo
This paper studies the introduction of sparse group LASSO (SGL) to the quantile regression framework. Additionally, a more flexible version, an adaptive SGL is proposed based on th…
Comparing Lasso and Adaptive Lasso in High-Dimensional Data: A Genetic Survival Analysis in Triple-Negative Breast Cancer
Pilar González-Barquero, Rosa E. Lillo, Ãlvaro Méndez-Civieta
In high-dimensional survival analysis, effective variable selection is crucial for both model interpretation and predictive performance. This paper investigates Cox regression with…