/// <summary>
/// Compute k-means clusters of the data.
/// </summary>
/// <param name="m">The number of clusters to compute.</param>
/// <returns>A description of the identified clusters.</returns>
public MeansClusteringResult MeansClustering(int m)
{
return(Multivariate.MeansClustering(storage, m));
}
/// <summary>
/// Computes the given sample raw moment.
/// </summary>
/// <param name="powers">The power to which each component should be raised.</param>
/// <returns>The specified moment.</returns>
/// <exception cref="ArgumentNullException"><paramref name="powers"/> is null.</exception>
/// <exception cref="DimensionMismatchException">The length of <paramref name="powers"/> is not
/// equal to the <see cref="Dimension"/> of the multivariate sample.</exception>
public double RawMoment(IReadOnlyList <int> powers)
{
return(Multivariate.RawMoment(storage, powers));
}
/// <summary>
/// Performs a principal component analysis of the data.
/// </summary>
/// <returns>The result of the principal component analysis.</returns>
/// <exception cref="InsufficientDataException">The number of data entries (<see cref="Count"/>) is
/// less than the number of variables (<see cref="Dimension"/>).</exception>
/// <seealso cref="PrincipalComponentAnalysis"/>
public PrincipalComponentAnalysis PrincipalComponentAnalysis()
{
return(Multivariate.PrincipalComponentAnalysis(storage));
}
/// <summary>
/// Computes the given sample raw moment.
/// </summary>
/// <param name="powers">The power to which each component should be raised.</param>
/// <returns>The specified moment.</returns>
public double RawMoment(params int[] powers)
{
return(Multivariate.RawMoment(storage, powers));
}