Background A common dataset was simulated and made available to participants of the XVI
th QTL-MAS workshop. Tasks for the participants were to detect QTLs affecting three traits, to …

Tremendous progress has been made in the last two decades in the area of high-
dimensional regression, especially in the “large p, small n” setting. Such sample starved …

Global-local shrinkage priors quickly found favor in the Bayesian community because of
their excellent empirical behaviour and the promise of fast implementations. Soon after …

Multivariate quantitative genetics provides a powerful framework for understanding patterns
and processes of phenotypic evolution. Quantitative genetics parameters, like trait …

In many applications, a parsimonious model is often preferred for better interpretability and
predictive performance. Online algorithms have been studied extensively for building such …

Bayesian shrinkage methods have generated a lot of recent interest as tools for high-
dimensional regression and model selection. These methods naturally facilitate tractable …

Abstract Model misspecification can compromise valid inference in conventional quantile
regression models. To address this issue, we consider two flexible model extensions for …

High-dimensional data, where the number of variables exceeds or is comparable to the
sample size, is now pervasive in many scientific applications. In recent years, Bayesian …

Selection and crossbreeding are the main breeding strategies used in animal or poultry
improvement programs. They involve the identification of individuals with the best genetic …

High-dimensional multivariate datasets, where the number of variables is larger than, or
comparable to the sample size, are now pervasive in many scientific applications. Sparsity is …