LR_classification: Binary classification with RG ditribution

In LauraMasiero/RiemannR: RiemannR - EEG-based BCI analysis with Riemannian geometry

Description

This function computes binary classification using a likelihood ratio, based on Riemann-Gauss distribution.

Usage

LR_classification(mu, sigma, scm_list)

Arguments

mu	a list containing the (geometric) mean of the two different classes.
sigma	a numeric vector containing the dispersion parameter of the two classes.
scm_list	a list containoing the sample covariance matrices to classify.

Value

It returns a list containing two elements:

lik_ratios	a list where each element is the likelihood ratio
classes	a numeric vector indicating the class estimated for every scm matrix.

Author(s)

Laura Masiero, email: [e-mail]

See Also

RG_distr

LauraMasiero/RiemannR documentation built on Sept. 29, 2020, 9:51 p.m.