/// <summary>
/// Generates a random vector of observations from the current distribution.
/// </summary>
///
/// <param name="samples">The number of samples to generate.</param>
/// <param name="result">The location where to store the samples.</param>
///
/// <returns>A random vector of observations drawn from this distribution.</returns>
///
public virtual int[][] Generate(int samples, int[][] result)
{
if (generator == null)
{
generator = MetropolisHasting.Discrete(Dimension, this);
}
return(generator.Generate(samples, result));
}
public virtual int[][] Generate(int samples, int[][] result, Random source)
{
if (generator == null)
{
generator = MetropolisHasting.Discrete(Dimension, this);
}
if (generator.RandomSource != source)
{
generator.RandomSource = source;
}
return(generator.Generate(samples, result));
}
public virtual double[][] Generate(int samples, double[][] result, Random source)
{
if (generator == null)
{
generator = new MetropolisHasting(Dimension, LogProbabilityDensityFunction);
}
if (generator.RandomSource != source)
{
generator.RandomSource = source;
}
return(Elementwise.Round(Generate(samples), result: result));
}
