computeLikelihoodRatioTest(modeledCovList, covList, m_constants, m_model)

function [pValue, testStatistic, df] = computeLikelihoodRatioTest(modeledCovList, covList, m_constants, m_model)

pValue = 0;
testStatistic = 0;
df = 0;

if isempty(modeledCovList)
    return
end

if strcmp(m_model, 'linear')
	for i = 1:m_constants.numGrp
        testStatistic = testStatistic + (m_constants.numElemPerGrp(i) - 1) * log(det(covList{i}));
	end
    testStatistic = (sum(m_constants.numElemPerGrp) - m_constants.numGrp )* log(det(modeledCovList{1})) - testStatistic;
else
    for i = 1:m_constants.numGrp
        testStatistic = testStatistic + (m_constants.numElemPerGrp(i) - 1)* log(det(modeledCovList{i}) / det(covList{i}));
	end
end

switch m_model
    case 'cpc'
        df = (m_constants.numGrp - 1) * m_constants.numVar * (m_constants.numVar - 1) / 2;
%         testStatistic = testStatistic + 2 * (m_constants.numGrp - 1) * m_constants.numVar; % AIC for Flury Decomposition of Chi Square 
    case 'proportional'
        df = (m_constants.numGrp - 1) * (m_constants.numVar^2 + m_constants.numVar - 2) / 2;
%         testStatistic = testStatistic + 2 * (m_constants.numGrp - 1); % AIC for Flury Decomposition of Chi Square
    case 'linear'
        df = (m_constants.numGrp - 1) * (m_constants.numVar^2 + m_constants.numVar) / 2;
end
    
pValue = 1 - chi2cdf(testStatistic, df);