ShiVa: Detection of Evolutionary Shifts in Both Optimal Value and Variance

Implements statistical methods for detecting evolutionary shifts in both the optimal trait value (mean) and evolutionary diffusion variance. The method uses an L1-penalized optimization framework to identify branches where shifts occur, and the shift magnitudes. It also supports the inclusion of measurement error. For more details, see Zhang, Ho, and Kenney (2023) <doi:10.48550/arXiv.2312.17480>.

Version:	1.0.1
Depends:	R (≥ 3.6.0)
Imports:	glmnet, psych, ape, phylolm, MASS, igraph
Suggests:	knitr, rmarkdown
Published:	2025-07-22
Author:	Wensha Zhang [aut, cre], Lam Si Tung Ho [aut], Toby Kenney [aut]
Maintainer:	Wensha Zhang <wn209685 at dal.ca>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	README
CRAN checks:	ShiVa results

Documentation:

Reference manual:	ShiVa.html , ShiVa.pdf
Vignettes:	ShiVa Example (source, R code)

Downloads:

Package source:	ShiVa_1.0.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): ShiVa_1.0.1.tgz, r-oldrel (x86_64): ShiVa_1.0.1.tgz

Linking:

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