… penalized approach to grouped longitudinal data and … Bayesian regression model, various
variable selection approaches have been proposed. In particular, the Bayesian group LASSO …

… function, we propose a group LASSO penalized SPR estimator for the varying coefficient
nonparametric transformation models, … (2018), we define a Bayesian information criterion (BIC) …

… new approach to Bayesian function selection in NVC models that … the nonparametric varying
coefficient spike-and-slab lasso (… Unlike the group lasso, group SCAD, and group MCP, this …

… -dimensional nonparametric models, a version of group lasso (cf… generalizes to using the
group lasso. We use the classical … high-dimensional bayesian varying coefficient models. arXiv …

… latent group structure (1.4) by estimating the number of groups K 0 … , a nonparametric estimation
of the time-varying coefficient … structure among the individual functional coefficients. The …

… and function estimation in nonparametric additive models. The … for Bayesian Group Lasso
, which we discuss in next section. … varying-coefficient model equipped with Bayesian group …

… : Consider the least informative nonparametric model for H 0 ( . … The objective function in
the group LASSO for Cox model … convex function to be minimized over the model parameter β …

… The spline approach also treats a nonparametric function as a linear function with the …
models can be used for the GPLVCMs. To incorporate the within-cluster correlation, we apply the …

… The group lasso estimator is defined as the solution to the … assumes that each regression
coefficient varies as a function … We review two popular classes of non-parametric estimation …

… To identify a possible semi-varying coefficient modelling … -zero constant coefficients and
functional coefficients which vary … The Bayesian information criterion has been extended to the …