Geneland is a computer program for statistical analysis of population genetics data. Its main goal is to detect population structure in form of systematic variation of allele frequency that can be detected from departure from Hardy-Weinberg and linkage equilibrium. Geneland requires individual multilocus genetic data that are optionally geo-referenced. It implements several models that can make use of both geographic and genetic informations to estimate the number of populations in a dataset and delineate their spatial organisation.
MPMM is a set of R functions to simulate and infer mixture of population matrix (Usher) matrix models. In construcion. see R codes http://onlinelibrary.wiley.com/store/10.1111/2041-210x.12019/asset/supinfo/mee312019-sup-0001-DataS1.pdf?v=1&s=325947e88d2db8ff28098642c50f7eab724c335c
Supervised Component Generalized Linear Regression (SCGLR) implements a new regression approach in the multivariate generalized linear framework. The method allows the joint modeling of random variables from different exponential family distributions, searching for common PLS-type components.
FLXMRglmnet(), This is a driver which allows fitting of mixtures of GLMs where the coefficients are penalized using the (adaptive) lasso or the elastic net by reusing functionality from package glmnet.
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