package umontreal.iro.lecuyer.probdistmulti;

import umontreal.iro.lecuyer.util.PrintfFormat;
import umontreal.iro.lecuyer.util.Num;

/**
 * Classes implementing continuous multi-dimensional distributions should inherit 
 * from this class. Such distributions are characterized by a density
 *  function 
 * f (x1, x2,…, xd);
 * thus the signature of a density method is supplied here.
 * All array indices start at 0.
 * 
 */
public abstract class ContinuousDistributionMulti {
   protected int dimension;



   /**
    * Returns 
    * f (x1, x2,…, xd), the probability density of
    *   X evaluated at the point
    *  x, where 
    * x = {x1, x2,…, xd}. The convention is that 
    *   
    * x[i - 1] = xi.
    * 
    * @param x value at which the density is evaluated
    * 
    *    @return density function evaluated at x
    * 
    */
   public abstract double density (double[] x);


   /**
    * Returns the dimension d of the distribution.
    * 
    */
   public int getDimension() {
      return dimension;
   }


   /**
    * Returns the mean vector of the distribution, defined as 
    * μi = E[Xi].
    * 
    */
   public abstract double[] getMean();


   /**
    * Returns the variance-covariance matrix of the distribution, defined as
    * 
   
    * σij = E[(Xi - μi)(Xj - μj)].
    * 
    */
   public abstract double[][] getCovariance();


   /**
    * Returns the correlation matrix of the distribution, defined as
    *       
    * ρij = σij/(σ_iiσ_jj)1/2.
    * 
    */
   public abstract double[][] getCorrelation();

}