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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 |
| DOI: | 10.32614/CRAN.package.ShiVa |
| 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 |
| Reference manual: | ShiVa.html , ShiVa.pdf |
| Vignettes: |
ShiVa Example (source, R code) |
| Package source: | ShiVa_1.0.1.tar.gz |
| Windows binaries: | r-devel: not available, r-release: ShiVa_1.0.1.zip, r-oldrel: ShiVa_1.0.1.zip |
| macOS binaries: | r-release (arm64): ShiVa_1.0.1.tgz, r-oldrel (arm64): ShiVa_1.0.1.tgz, r-release (x86_64): ShiVa_1.0.1.tgz, r-oldrel (x86_64): ShiVa_1.0.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.