DistNegBinomial.java
package nl.tudelft.simulation.jstats.distributions;
import org.djutils.exceptions.Throw;
import nl.tudelft.simulation.jstats.math.ProbMath;
import nl.tudelft.simulation.jstats.streams.StreamInterface;
/**
* The Negative Binomial distribution. It is also known as the Pascal distribution or Pólya distribution. It gives the
* probability of x failures where there are s-1 successes in a total of x+s-1 Bernoulli trials, and trial (x+s) is a success.
* The chance for success is p for each trial. For more information on this distribution see
* <a href="https://mathworld.wolfram.com/NegativeBinomialDistribution.html">
* https://mathworld.wolfram.com/NegativeBinomialDistribution.html </a>
* <p>
* Copyright (c) 2002-2024 Delft University of Technology, Jaffalaan 5, 2628 BX Delft, the Netherlands. All rights reserved. See
* for project information <a href="https://simulation.tudelft.nl/" target="_blank"> https://simulation.tudelft.nl</a>. The DSOL
* project is distributed under a three-clause BSD-style license, which can be found at
* <a href="https://https://simulation.tudelft.nl/dsol/docs/latest/license.html" target="_blank">
* https://https://simulation.tudelft.nl/dsol/docs/latest/license.html</a>.
* </p>
* @author <a href="https://www.linkedin.com/in/peterhmjacobs">Peter Jacobs </a>
* @author <a href="https://www.tudelft.nl/averbraeck">Alexander Verbraeck</a>
*/
public class DistNegBinomial extends DistDiscrete
{
/** */
private static final long serialVersionUID = 1L;
/** s is the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success. */
private int s;
/** p is the probability of success for each individual trial in the negative binomial distribution. */
private double p;
/** lnp is a helper variable equal to ln(1-p) to avoid repetitive calculation. */
private double lnp;
/**
* constructs a new negative binomial distribution.
* @param stream StreamInterface; the random number stream
* @param s int; the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success
* @param p double; the probability of success for each individual trial in the negative binomial distribution
* @throws IllegalArgumentException when s <= 0 or p <= 0 or p >= 1
*/
public DistNegBinomial(final StreamInterface stream, final int s, final double p)
{
super(stream);
Throw.when(s <= 0 || p <= 0.0 || p >= 1.0, IllegalArgumentException.class,
"Error NegBinomial - s<=0 or p<=0.0 or p>=1.0");
this.s = s;
this.p = p;
this.lnp = Math.log(1.0 - this.p);
}
/** {@inheritDoc} */
@Override
public long draw()
{
long x = 0;
for (int i = 0; i < this.s; i++)
{
double u = this.stream.nextDouble();
x = x + (long) (Math.floor(Math.log(u) / this.lnp));
}
return x;
}
/** {@inheritDoc} */
@Override
public double probability(final long observation)
{
if (observation >= 0)
{
return ProbMath.combinations(this.s + observation - 1, observation) * Math.pow(this.p, this.s)
* Math.pow(1 - this.p, observation);
}
return 0.0;
}
/**
* Return the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success.
* @return int; the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success
*/
public int getS()
{
return this.s;
}
/**
* Return the probability of success for each individual trial in the negative binomial distribution.
* @return double; the probability of success for each individual trial in the negative binomial distribution
*/
public double getP()
{
return this.p;
}
/** {@inheritDoc} */
@Override
public String toString()
{
return "NegBinomial(" + this.s + "," + this.p + ")";
}
}