package umontreal.iro.lecuyer.randvar;
import umontreal.iro.lecuyer.rng.*;
import umontreal.iro.lecuyer.probdist.*;


/**
 * This class implements noncentral chi square random variate generators 
 * using Poisson and central chi square generators. It uses the following algorithm:
 * generate a random integer 
 * J∼Poisson(λ/2) from a Poisson 
 * distribution, generate a random real 
 * X∼Γ(j + ν/2, 1/2) from a 
 * gamma distribution, then return X. 
 * Here ν is the number of degrees of freedom and 
 * λ is the noncentrality parameter.
 * 
 * 

 * To generate the Poisson variates, one 
 * uses tabulated inversion for 
 * λ < 10, and the acceptance complement 
 * method for 
 * λ >= 10, as in
 * (see class {@link umontreal.iro.lecuyer.randvar.PoissonTIACGen PoissonTIACGen}).
 * To generate the gamma variates, one 
 * uses acceptance-rejection for α < 1, and acceptance-complement
 * for 
 * α >= 1, as proposed  in
 * (see class {@link umontreal.iro.lecuyer.randvar.GammaAcceptanceRejectionGen GammaAcceptanceRejectionGen}).
 * 
 */
public class ChiSquareNoncentralPoisGen extends ChiSquareNoncentralGen  {
//   protected RandomStream aux; 



   /**
    * Creates a noncentral chi square random variate generator 
    * with ν = nu degrees of freedom and noncentrality parameter
    * λ = lambda using stream stream, as described above.
    * 
    */
   public ChiSquareNoncentralPoisGen (RandomStream stream,
                                      double nu, double lambda)  {
      super (stream, null);
      setParams (nu, lambda);
   }
 
  
   public double nextDouble() {
      return poisGenere (stream, nu, lambda);
   }

   /**
    * Generates a variate from the noncentral chi square
    *    distribution with
    *    parameters ν = nu and λ = lambda using
    *    stream stream, as described above.
    * 
    */
   public static double nextDouble (RandomStream stream,
                                    double nu, double lambda)  {
      return poisGenere (stream, nu, lambda);
   }


//>>>>>>>>>>>>>>>>>>>>  P R I V A T E S    M E T H O D S   <<<<<<<<<<<<<<<<<<<< 

   private static double poisGenere (RandomStream s, double nu, double lambda) {
      int j = PoissonTIACGen.nextInt (s, 0.5*lambda);
      return GammaAcceptanceRejectionGen.nextDouble (s, 0.5*nu + j, 0.5);
   }

}