1 package nl.tudelft.simulation.jstats.distributions;
2
3 import org.djutils.exceptions.Throw;
4
5 import nl.tudelft.simulation.jstats.math.ProbMath;
6 import nl.tudelft.simulation.jstats.streams.StreamInterface;
7
8 /**
9 * The Negative Binomial distribution. It is also known as the Pascal distribution or Pólya distribution. It gives the
10 * 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.
11 * The chance for success is p for each trial. For more information on this distribution see
12 * <a href="https://mathworld.wolfram.com/NegativeBinomialDistribution.html">
13 * https://mathworld.wolfram.com/NegativeBinomialDistribution.html </a>
14 * <p>
15 * Copyright (c) 2002-2025 Delft University of Technology, Jaffalaan 5, 2628 BX Delft, the Netherlands. All rights reserved. See
16 * for project information <a href="https://simulation.tudelft.nl/dsol/manual/" target="_blank">DSOL Manual</a>. The DSOL
17 * project is distributed under a three-clause BSD-style license, which can be found at
18 * <a href="https://simulation.tudelft.nl/dsol/docs/latest/license.html" target="_blank">DSOL License</a>.
19 * </p>
20 * @author <a href="https://www.linkedin.com/in/peterhmjacobs">Peter Jacobs </a>
21 * @author <a href="https://github.com/averbraeck">Alexander Verbraeck</a>
22 */
23 public class DistNegBinomial extends DistDiscrete
24 {
25 /** */
26 private static final long serialVersionUID = 1L;
27
28 /** s is the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success. */
29 private int s;
30
31 /** p is the probability of success for each individual trial in the negative binomial distribution. */
32 private double p;
33
34 /** lnp is a helper variable equal to ln(1-p) to avoid repetitive calculation. */
35 private double lnp;
36
37 /**
38 * constructs a new negative binomial distribution.
39 * @param stream StreamInterface; the random number stream
40 * @param s int; the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success
41 * @param p double; the probability of success for each individual trial in the negative binomial distribution
42 * @throws IllegalArgumentException when s <= 0 or p <= 0 or p >= 1
43 */
44 public DistNegBinomial(final StreamInterface stream, final int s, final double p)
45 {
46 super(stream);
47 Throw.when(s <= 0 || p <= 0.0 || p >= 1.0, IllegalArgumentException.class,
48 "Error NegBinomial - s<=0 or p<=0.0 or p>=1.0");
49 this.s = s;
50 this.p = p;
51 this.lnp = Math.log(1.0 - this.p);
52 }
53
54 @Override
55 public long draw()
56 {
57 long x = 0;
58 for (int i = 0; i < this.s; i++)
59 {
60 double u = this.stream.nextDouble();
61 x = x + (long) (Math.floor(Math.log(u) / this.lnp));
62 }
63 return x;
64 }
65
66 @Override
67 public double probability(final long observation)
68 {
69 if (observation >= 0)
70 {
71 return ProbMath.combinations(this.s + observation - 1, observation) * Math.pow(this.p, this.s)
72 * Math.pow(1 - this.p, observation);
73 }
74 return 0.0;
75 }
76
77 /**
78 * Return the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success.
79 * @return int; the number of successes in the sequence of (x+n) trials, where trial (x+n) is a success
80 */
81 public int getS()
82 {
83 return this.s;
84 }
85
86 /**
87 * Return the probability of success for each individual trial in the negative binomial distribution.
88 * @return double; the probability of success for each individual trial in the negative binomial distribution
89 */
90 public double getP()
91 {
92 return this.p;
93 }
94
95 @Override
96 public String toString()
97 {
98 return "NegBinomial(" + this.s + "," + this.p + ")";
99 }
100 }