Fused-ANOVA: a package to fit weighted fusion penalties at large scale
Fused-ANOVA is a penalized method that solves the one-way ANOVA problem by collapsing the coefficients of K conditions. It reconstructs a balanced tree structure between the condition with a homotopy algorithm.
For a class of weights implemented here, our homotopy algorithm is in K log(K). These weights induce a balanced tree structure and simplify the interpretation of the results. The package contains an illustrating phenotypic data set: given a trait, we reconstruct a balanced tree structure and assess its agreement with the known phylogeny. More in the vignette.
Chiquet J, Gutierrez P, Rigaill G: Fast tree inference with weighted fusion penalties, Journal of Computational and Graphical Statistics 205–216, 2017. PDF version