plda: Poisson discriminant analysis.

In mdelhey/plda: poisson discriminant analysis

Description

Poisson discriminant analysis.

Usage

plda(X, y, type = c("linear", "quadratic", "poisson", "poisson.seq"),
  size.factor = c("mle", "quantile", "medratio"), prior = c("uniform",
  "proportion"))

Arguments

X	Matrix of predictors.
y	Factor vector of class or group labels.
type	Type of discriminant analysis to be performed. Linear assumes that all population class covariances are equal. Quadratic estimates each population class covariance separately. Linear and Quadratic assume predictors are normally distributed (i.e. continous data). Poisson models count data.
size.factor
prior	Type of prior probability. "Uniform" assumes that all classes are equally likely. "Proportion" estimates the prior probability of each class from their proportion in the training data.

Value

List of class "plda" containing the classifier results.

mdelhey/plda documentation built on May 22, 2019, 3:24 p.m.