2 papers
stat.ME2026
Parsimonious Subset Selection for Generalized Linear Models with Biomedical Applications
Anant Mathur, Benoit Liquet, Samuel Muller +1
High-dimensional biomedical studies require models that are simultaneously accurate, sparse, and interpretable, yet exact best subset selection for generalized linear models is com…
stat.ME2024
A maximum penalised likelihood approach for semiparametric accelerated failure time models with time-varying covariates and partly interval censoring
Aishwarya Bhaskaran, Ding Ma, Benoit Liquet +4
Accelerated failure time (AFT) models are frequently used to model survival data, providing a direct quantification of the relationship between event times and covariates. These mo…