Package: bifrost 0.1.4

bifrost: 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.

Authors:Jacob S. Berv [aut, cre, cph, fnd], Nathan Fox [aut], Matt J. Thorstensen [aut], Henry Lloyd-Laney [aut], Emily M. Troyer [aut], Rafael A. Rivero-Vega [aut], Stephen A. Smith [aut, fnd], Matt Friedman [aut, fnd], David F. Fouhey [aut, fnd], Brian C. Weeks [aut, fnd]