/// <summary>
/// N(mu, sigma)
/// </summary>
/// <param name="l">lower bound</param>
/// <param name="u">upper bound</param>
public MultivariateNormalDistribution(PZMath_vector m, PZMath_matrix s)
{
dimension = m.Size;
mu = new PZMath_vector(dimension);
mu.MemCopyFrom(m);
sigma = new PZMath_matrix(dimension, dimension);
sigma.MemCopyFrom(s);
if (dimension != sigma.RowCount || dimension != sigma.ColumnCount)
throw new ApplicationException("MultivariateNormalDistribution::MultivariateNormalDistribution(), mu and sigma in different dimension!");
Init();
}
/// <summary>
/// sigma is a diagonal matrix
/// </summary>
/// <param name="m"></param>
/// <param name="diag"></param>
public MultivariateNormalDistribution(PZMath_vector m, PZMath_vector diag)
{
if (m.Size != diag.Size)
throw new ApplicationException("MultivariateNormalDistribution::MultivariateNormalDistribution(), mu and sigma in different dimension!");
dimension = m.Size;
mu = new PZMath_vector(dimension);
mu.MemCopyFrom(m);
sigma = new PZMath_matrix(dimension, dimension);
for (int i = 0; i < dimension; i ++)
sigma[i, i] = diag[i];
Init();
}