qdaClassification: qdaClassification

In optimalFlow: optimalFlow

Description

Gives quadratic discriminant scores to the points in data for a multivariate normal.

Usage

qdaClassification(normal, data)

Arguments

normal	A list with arguments mean, covaruance and weight.
data	Data frame or matrix on which to perform qda.

Value

A score for each point.

Examples

data.qda = cbind(rnorm(50), rnorm(50))
exp(qdaClassification(list(mean = c(0,0), cov = diag(1,2), weight = 1), data.qda))

optimalFlow documentation built on Nov. 8, 2020, 6:59 p.m.