Discriminant Analysis for Evolutionary Inference

Discriminant Analysis (DA) for evolutionary inference (Qin, X. et al, 2020, ), especially for population genetic structure and community structure inference. This package incorporates the commonly used linear and non-linear, local and global supervised learning approaches (discriminant analysis), including Linear Discriminant Analysis of Kernel Principal Components (LDAKPC), Local (Fisher) Linear Discriminant Analysis (LFDA), Local (Fisher) Discriminant Analysis of Kernel Principal Components (LFDAKPC) and Kernel Local (Fisher) Discriminant Analysis (KLFDA). These discriminant analyses can be used to do ecological and evolutionary inference, including demography inference, species identification, and population/community structure inference.


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install.packages("DA")

1.2.0 by Xinghu Qin, 3 months ago


https://xinghuq.github.io/DA/index.html


Report a bug at https://github.com/xinghuq/DA/issues


Browse source code at https://github.com/cran/DA


Authors: Xinghu Qin [aut, cre, cph]


Documentation:   PDF Manual  


GPL-3 license


Imports adegenet, lfda, MASS, kernlab, klaR, plotly, rARPACK, grDevices, stats, utils

Suggests knitr, testthat, rmarkdown

System requirements: GNU make


See at CRAN