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


/**
 * This class implements random variate generators for the 
 * log-logistic distribution with shape parameter 
 * α > 0
 * and scale parameter β > 0.
 * The density function of this distribution is
 * 
 * 

 * 

 * f (x) = (α(x/β)α-1)/(β[1 + (x/β)α]2)                for x > 0.
 * 

 * 
 */
public class LoglogisticGen extends RandomVariateGen  {
   protected double alpha;
   protected double beta;




   /**
    * Creates a log-logistic random variate generator with parameters
    *   α = alpha and β = beta, using stream s.
    * 
    */
   public LoglogisticGen (RandomStream s, double alpha, double beta)  {
      super (s, new LoglogisticDist(alpha, beta));
      setParams (alpha, beta);
   }


   /**
    * Creates a new generator for the distribution dist,
    *      using stream s.
    * 
    */
   public LoglogisticGen (RandomStream s, LoglogisticDist dist)  {
      super (s, dist);
      if (dist != null)
         setParams (dist.getAlpha(), dist.getBeta());
   }
    

   /**
    * Generates a variate from the log-logistic distribution
    *    with shape parameter 
    * α > 0 and scale parameter β > 0.
    * 
    */
   public static double nextDouble (RandomStream s,
                                    double alpha, double beta) {
      return LoglogisticDist.inverseF (alpha, beta, s.nextDouble());
   }


   /**
    * Returns the parameter α of this object.
    * 
    */
   public double getAlpha() {
      return alpha;
   }


   /**
    * Returns the parameter β of this object.
    * 
    */
   public double getBeta() {
      return beta;
   }


   protected void setParams (double alpha, double beta) {
      if (alpha <= 0.0)
         throw new IllegalArgumentException ("alpha <= 0");
      if (beta <= 0.0)
         throw new IllegalArgumentException ("beta <= 0");
      this.alpha = alpha;
      this.beta = beta;
   }
}