001    /*
002     * Licensed to the Apache Software Foundation (ASF) under one or more
003     * contributor license agreements.  See the NOTICE file distributed with
004     * this work for additional information regarding copyright ownership.
005     * The ASF licenses this file to You under the Apache License, Version 2.0
006     * (the "License"); you may not use this file except in compliance with
007     * the License.  You may obtain a copy of the License at
008     *
009     *      http://www.apache.org/licenses/LICENSE-2.0
010     *
011     * Unless required by applicable law or agreed to in writing, software
012     * distributed under the License is distributed on an "AS IS" BASIS,
013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014     * See the License for the specific language governing permissions and
015     * limitations under the License.
016     */
017    package org.apache.commons.math.distribution;
018    
019    /**
020     * Interface for discrete distributions of integer-valued random variables.
021     *
022     * @version $Id: IntegerDistribution.java 1178295 2011-10-03 04:36:27Z psteitz $
023     */
024    public interface IntegerDistribution extends DiscreteDistribution {
025        /**
026         * For a random variable {@code X} whose values are distributed according
027         * to this distribution, this method returns {@code P(X = x)}. In other
028         * words, this method represents the probability mass function for the
029         * distribution.
030         *
031         * @param x Value at which the probability density function is evaluated.
032         * @return the value of the probability density function at {@code x}.
033         */
034        double probability(int x);
035    
036        /**
037         * For a random variable {@code X} whose values are distributed according
038         * to this distribution, this method returns {@code P(X <= x)}.  In other
039         * words, this method represents the probability distribution function, or
040         * PDF for the distribution.
041         *
042         * @param x Value at which the PDF is evaluated.
043         * @return PDF for this distribution.
044         */
045        double cumulativeProbability(int x);
046    
047        /**
048         * For this distribution, {@code X}, this method returns
049         * {@code P(x0 <= X <= x1)}.
050         *
051         * @param x0 the inclusive, lower bound
052         * @param x1 the inclusive, upper bound
053         * @return the cumulative probability.
054         * @throws IllegalArgumentException if {@code x0 > x1}.
055         */
056        double cumulativeProbability(int x0, int x1);
057    
058        /**
059         * For this distribution, {@code X}, this method returns the largest
060         * {@code x} such that {@code P(X <= x) <= p}.
061         * <br/>
062         * Note that this definition implies:
063         * <ul>
064         *  <li> If there is a minimum value, {@code m}, with positive
065         *   probability under (the density of) {@code X}, then {@code m - 1} is
066         *   returned by {@code inverseCumulativeProbability(0).}  If there is
067         *   no such value {@code m},  {@code Integer.MIN_VALUE} is returned.
068         *  </li>
069         *  <li> If there is a maximum value, {@code M}, such that
070         *   {@code P(X <= M) = 1}, then {@code M} is returned by
071         *   {@code inverseCumulativeProbability(1)}.
072         *   If there is no such value, {@code M}, {@code Integer.MAX_VALUE} is
073         *   returned.
074         *  </li>
075         * </ul>
076         *
077         * @param p Cumulative probability.
078         * @return the largest {@code x} such that {@code P(X < x) <= p}.
079         * @throws IllegalArgumentException if {@code p} is not between 0 and 1
080         * (inclusive).
081         */
082        int inverseCumulativeProbability(double p);
083    
084        /**
085         * Reseed the random generator used to generate samples.
086         *
087         * @param seed New seed.
088         * @since 3.0
089         */
090        void reseedRandomGenerator(long seed);
091    
092        /**
093         * Generate a random value sampled from this distribution.
094         *
095         * @return a random value.
096         * @since 3.0
097         */
098        int sample();
099    
100        /**
101         * Generate a random sample from the distribution.
102         *
103         * @param sampleSize number of random values to generate.
104         * @return an array representing the random sample.
105         * @throws org.apache.commons.math.exception.NotStrictlyPositiveException
106         * if {@code sampleSize} is not positive.
107         * @since 3.0
108         */
109        int[] sample(int sampleSize);
110    }