This article develops a sparsity-inducing version of Bayesian Causal Forests, a recently proposed nonparametric causal regression model that employs Bayesian Additive Regression Trees and is specifica
A single-step approach to obtain genomic prediction was firstly proposed in 2009. Many studies have investigated the components of GEBV accuracy in genomic selection. However, it is still unclear how
In the context of a Gaussian multiple regression model, we address the problem of variable selection when in the list of potential predictors there are factors, that is, categorical variables. We adop
The 1st column shows whether the smaller or larger priors were used; the 3rd column shows the number of times (out of 7000 data sets) the true (i.e., the data-generating) model had the highest posteri