Java tutorial
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.commons.math.distribution; import org.apache.commons.math.MathException; /** * Interface for discrete distributions of integer-valued random variables. * * @version $Revision: 949535 $ $Date: 2010-05-30 19:00:15 +0200 (dim. 30 mai 2010) $ */ public interface IntegerDistribution extends DiscreteDistribution { /** * For a random variable X whose values are distributed according * to this distribution, this method returns P(X = x). In other words, this * method represents the probability mass function for the distribution. * * @param x the value at which the probability density function is evaluated. * @return the value of the probability density function at x */ double probability(int x); /** * For a random variable X whose values are distributed according * to this distribution, this method returns P(X ≤ x). In other words, * this method represents the probability distribution function, or PDF * for the distribution. * * @param x the value at which the PDF is evaluated. * @return PDF for this distribution. * @throws MathException if the cumulative probability can not be * computed due to convergence or other numerical errors. */ double cumulativeProbability(int x) throws MathException; /** * For this distribution, X, this method returns P(x0 ≤ X ≤ x1). * @param x0 the inclusive, lower bound * @param x1 the inclusive, upper bound * @return the cumulative probability. * @throws MathException if the cumulative probability can not be * computed due to convergence or other numerical errors. * @throws IllegalArgumentException if x0 > x1 */ double cumulativeProbability(int x0, int x1) throws MathException; /** * For this distribution, X, this method returns the largest x such that * P(X ≤ x) <= p. * <p> * Note that this definition implies: <ul> * <li> If there is a minimum value, <code>m</code>, with positive * probability under (the density of) X, then <code>m - 1</code> is * returned by <code>inverseCumulativeProbability(0).</code> If there is * no such value <code>m, Integer.MIN_VALUE</code> is * returned.</li> * <li> If there is a maximum value, <code>M</code>, such that * P(X ≤ M) =1, then <code>M</code> is returned by * <code>inverseCumulativeProbability(1).</code> * If there is no such value, <code>M, Integer.MAX_VALUE</code> is * returned.</li></ul></p> * * @param p the cumulative probability. * @return the largest x such that P(X ≤ x) <= p * @throws MathException if the inverse cumulative probability can not be * computed due to convergence or other numerical errors. * @throws IllegalArgumentException if p is not between 0 and 1 (inclusive) */ int inverseCumulativeProbability(double p) throws MathException; }