Shimizu, Taciana K. O.
Suzuki, Adriano K.
Total Authors: 3
 Univ Sao Paulo, ICMC, Dept Appl Math & Stat, Sao Carlos, SP - Brazil
Total Affiliations: 1
STATISTICAL METHODS IN MEDICAL RESEARCH;
Web of Science Citations:
There are considerable challenges in analyzing large-scale compositional data. In this paper, we introduce the Spike-and-Slab Lasso linear regression in the presence of compositional covariates for parameter estimation and variable selection. We consider the well-known isometric log-ratio (ilr) coordinates to avoid misleading statistical inference. The separable and non-separable (adaptative) Spike-and-Slab Lasso penalties are compared to verify the advantages of each approach. The proposed method is illustrated on simulated and on real Brazilian child malnutrition data. (AU)