Branch-Level Inference Framework for Recognizing Optimal Shifts in Traits // Methods for detecting and visualizing cladogenic shifts in multivariate trait data on phylogenies. Implements penalized-likelihood multivariate generalized least squares models, enabling analyses of high-dimensional trait datasets and large trees via searchOptimalConfiguration(). Includes a greedy step-wise shift-search algorithm following approaches developed in Smith et al. (2023) doi:10.1111/nph.19099 and Berv et al. (2024) doi:10.1126/sciadv.adp0114. Methods build on multivariate GLS approaches described in Clavel et al. (2019) doi:10.1093/sysbio/syy045 and implemented in the mvgls() function from the 'mvMORPH' package. Documentation and vignettes are available at https://jakeberv.com/bifrost/, including worked examples for the jaw-shape dataset.