public void FindMaximize_MaxiumOccursAtBoundary_ReturnsCorrectValue()
{
OneDimensionalFunction function = x => - x * x * x * x - x * x * x + 11 * x * x + 9 * x - 18;
OneDimensionalFunction derivativeFunction = x => - 4 * x * x * x - 3 * x * x + 22 * x + 9;
double lowerBound = -5;
double upperBound = 5;
GlobalMaximizer maximizer = new GlobalMaximizer(function, derivativeFunction, lowerBound, upperBound);
var maxLocation = maximizer.FindPosOfMaximum();
double expectedMaxPostion = 2.20582;
Assert.AreEqual(expectedMaxPostion, maxLocation, Tolerance);
}
public void FindMaximize_FunctionWithSeveralEqualGlobalMinima_ReturnsAValueWhichGivesMax()
{
OneDimensionalFunction function = Math.Sin;
OneDimensionalFunction derivativeFunction = Math.Cos;
double lowerBound = -5;
double upperBound = 5;
GlobalMaximizer maximizer = new GlobalMaximizer(function, derivativeFunction, lowerBound, upperBound);
var x = maximizer.FindPosOfMaximum();
double max = function(x);
double expectedMax = 1;
Assert.AreEqual(expectedMax, max, Tolerance);
}
public double GetMle(List <int> responseVector)
{
LogLikelihoodFunction logLikelihoodFunction = new LogLikelihoodFunction(_modelParametersList);
//const double initialGuess = 0;
OneDimensionalFunction function = x => logLikelihoodFunction.LogLikelihood(responseVector, x);
OneDimensionalFunction firstDerivativeFunction = x => logLikelihoodFunction.LogLikelihoodFirstDerivative(responseVector, x);
//OneDimensionalFunction secondDerivativeFunction = x => logLikelihoodFunction.LogLikelihoodSecondDerivative(responseVector, x);
//NewtonRhapsonSolver rootSolver = new NewtonRhapsonSolver(firstDerivativeFunction, secondDerivativeFunction, initialGuess);
//BisectionSolver rootSolver = new BisectionSolver(firstDerivativeFunction, -6, 6);
//double mle = rootSolver.FindRoot();
//double mle = rootSolver.FindRoot();
GlobalMaximizer globalMaximizer = new GlobalMaximizer(function, firstDerivativeFunction, -6, 6, _gradientDescentTolerance);
var mle = globalMaximizer.FindPosOfMaximum();
return(mle);
}