Skip to main content

Likelihood Ratio Statistic

Edited by: Published: 2010
+- LessMore information
Download PDF

The likelihood ratio statistic evaluates the relative plausibility of two competing hypotheses on the basis of a collection of sample data. The favored hypothesis is determined by whether the ratio is greater than or less than one.

To introduce the likelihood ratio, suppose that yOBS denotes a vector of observed data. Assume that a parametric joint density is postulated for the random vector Y corresponding to the realization yOBS. Let f(y; θ) represent this density, with parameter vector θ. The likelihood of θ based on the data yOBS is defined as the joint density:

Although the likelihood and the density are the same function, they are viewed differently: The density f(y; θ) assigns probabilities to various outcomes for the random vector Y based on a fixed value ...

Looks like you do not have access to this content.

Reader's Guide

  • All
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z

      Copy and paste the following HTML into your website