kmatrixGauss

Input data matrix or dataframe

The Gaussian kernel parameter

sigma

This function estimates Gaussian kernel computation for klfda, which maps the original data space to non-linear and higher dimensions. See the deatils of kmatrixGauss from lfda.

Discriminant Analysis (DA) for evolutionary inference (Qin, X. et al, 2020, <doi:10.22541/au.159256808.83862168>), 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.

kmatrixGauss: Estimating Gaussian Kernel matrix

Description

Usage

Arguments

Value

Details

References