public void CanCreateNormalGamma(double meanLocation, double meanScale, double precShape, double precInvScale)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
Assert.AreEqual(meanLocation, ng.MeanLocation);
Assert.AreEqual(meanScale, ng.MeanScale);
Assert.AreEqual(precShape, ng.PrecisionShape);
Assert.AreEqual(precInvScale, ng.PrecisionInverseScale);
}
public void CanGetMeanLocation(double meanLocation, double meanScale, double precShape, double precInvScale)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
Assert.AreEqual(meanLocation, ng.MeanLocation);
}
public void CanGetDensityAndDensityLn(double meanLocation, double meanScale, double precShape, double precInvScale)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
Assert.AreEqual(ng.DensityLn(meanLocation, precShape), Math.Log(ng.Density(meanLocation, precShape)), 1e-14);
}
public void SamplesFollowsCorrectDistribution()
{
var cd = new NormalGamma(1.0, 4.0, 3.0, 3.5);
// Sample from the distribution.
var samples = cd.Samples().Take(CommonDistributionTests.NumberOfTestSamples).ToArray();
// Extract the mean and precisions.
var means = samples.Select(mp => mp.Mean).ToArray();
var precs = samples.Select(mp => mp.Precision).ToArray();
var meanMarginal = cd.MeanMarginal();
var precMarginal = cd.PrecisionMarginal();
// Check the precision distribution.
CommonDistributionTests.ContinuousVapnikChervonenkisTest(
CommonDistributionTests.ErrorTolerance,
CommonDistributionTests.ErrorProbability,
precs,
precMarginal);
// Check the mean distribution.
CommonDistributionTests.ContinuousVapnikChervonenkisTest(
CommonDistributionTests.ErrorTolerance,
CommonDistributionTests.ErrorProbability,
means,
meanMarginal);
}
public void ValidateVariance(double meanLocation, double meanScale, double precShape, double precInvScale)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
var x = precInvScale / (meanScale * (precShape - 1));
var t = precShape / Math.Sqrt(precInvScale);
Assert.AreEqual(x, ng.Variance.Mean);
Assert.AreEqual(t, ng.Variance.Precision);
}
public void HasRandomSource()
{
var ng = new NormalGamma(0.0, 1.0, 1.0, 1.0);
Assert.IsNotNull(ng.RandomSource);
}
public void CanGetPrecisionMarginal(double meanLocation, double meanScale, double precShape, double precInvScale)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
var pm = ng.PrecisionMarginal();
Assert.AreEqual(precShape, pm.Shape);
Assert.AreEqual(precInvScale, pm.Rate);
}
public void CanGetMeanMarginal(double meanLocation, double meanScale, double precShape, double precInvScale, double meanMarginalMean, double meanMarginalScale, double meanMarginalDoF)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
var mm = ng.MeanMarginal();
Assert.AreEqual(meanMarginalMean, mm.Location);
Assert.AreEqual(meanMarginalScale, mm.Scale);
Assert.AreEqual(meanMarginalDoF, mm.DegreesOfFreedom);
}
public void CanGetPrecisionShape(double meanLocation, double meanScale, double precShape, double precInvScale)
{
var ng = new NormalGamma(meanLocation, meanScale, precShape, precInvScale);
Assert.AreEqual(precShape, ng.PrecisionShape);
}