/// <summary>
/// Gibbs message to 'sample'
/// </summary>
/// <param name="Mean">Constant value for 'mean'.</param>
/// <param name="Precision">Constant value for 'precision'.</param>
/// <param name="result">Modified to contain the outgoing message</param>
/// <returns><paramref name="result"/></returns>
/// <remarks><para>
/// The outgoing message is the factor viewed as a function of 'sample' conditioned on the given values.
/// </para></remarks>
public static VectorGaussian SampleConditional(Vector Mean, PositiveDefiniteMatrix Precision, VectorGaussian result)
{
result.SetMeanAndPrecision(Mean, Precision);
return result;
}
public static VectorGaussian ExtractVectorPart(VectorGaussianWishart gaussianWishart, VectorGaussian result)
{
if (gaussianWishart.IsVectorMarginalUniform())
{
return VectorGaussian.Uniform(2);
}
double firstShape, secondPrecisionScale;
PositiveDefiniteMatrix firstRate;
Vector secondLocation;
gaussianWishart.ExtractParameters(out firstShape, out firstRate, out secondLocation, out secondPrecisionScale);
result.SetMeanAndPrecision(secondLocation, MathHelpers.Invert(firstRate) * (firstShape * secondPrecisionScale));
return result;
}