Adaptive Fused LASSO in Grouped Quantile Regression
classification
🧮 math.ST
stat.TH
keywords
groupsquantileadaptiveestimatorfusedgroupedlassosparsity
read the original abstract
This paper considers quantile model with grouped explanatory variables. In order to have the sparsity of the parameter groups but also the sparsity between two successive groups of variables, we propose and study an adaptive fused group LASSO quantile estimator. The number of variable groups can be fixed or divergent. We find the convergence rate under classical assumptions and we show that the proposed estimator satisfies the oracle properties.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.