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+/*
+ * 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.math3.distribution;
+
+import org.apache.commons.math3.exception.NotPositiveException;
+import org.apache.commons.math3.exception.OutOfRangeException;
+import org.apache.commons.math3.exception.util.LocalizedFormats;
+import org.apache.commons.math3.random.RandomGenerator;
+import org.apache.commons.math3.random.Well19937c;
+import org.apache.commons.math3.special.Beta;
+import org.apache.commons.math3.util.FastMath;
+
+/**
+ * Implementation of the binomial distribution.
+ *
+ * @see <a href="http://en.wikipedia.org/wiki/Binomial_distribution">Binomial distribution
+ *     (Wikipedia)</a>
+ * @see <a href="http://mathworld.wolfram.com/BinomialDistribution.html">Binomial Distribution
+ *     (MathWorld)</a>
+ */
+public class BinomialDistribution extends AbstractIntegerDistribution {
+    /** Serializable version identifier. */
+    private static final long serialVersionUID = 6751309484392813623L;
+
+    /** The number of trials. */
+    private final int numberOfTrials;
+
+    /** The probability of success. */
+    private final double probabilityOfSuccess;
+
+    /**
+     * Create a binomial distribution with the given number of trials and probability of success.
+     *
+     * <p><b>Note:</b> this constructor will implicitly create an instance of {@link Well19937c} as
+     * random generator to be used for sampling only (see {@link #sample()} and {@link
+     * #sample(int)}). In case no sampling is needed for the created distribution, it is advised to
+     * pass {@code null} as random generator via the appropriate constructors to avoid the
+     * additional initialisation overhead.
+     *
+     * @param trials Number of trials.
+     * @param p Probability of success.
+     * @throws NotPositiveException if {@code trials < 0}.
+     * @throws OutOfRangeException if {@code p < 0} or {@code p > 1}.
+     */
+    public BinomialDistribution(int trials, double p) {
+        this(new Well19937c(), trials, p);
+    }
+
+    /**
+     * Creates a binomial distribution.
+     *
+     * @param rng Random number generator.
+     * @param trials Number of trials.
+     * @param p Probability of success.
+     * @throws NotPositiveException if {@code trials < 0}.
+     * @throws OutOfRangeException if {@code p < 0} or {@code p > 1}.
+     * @since 3.1
+     */
+    public BinomialDistribution(RandomGenerator rng, int trials, double p) {
+        super(rng);
+
+        if (trials < 0) {
+            throw new NotPositiveException(LocalizedFormats.NUMBER_OF_TRIALS, trials);
+        }
+        if (p < 0 || p > 1) {
+            throw new OutOfRangeException(p, 0, 1);
+        }
+
+        probabilityOfSuccess = p;
+        numberOfTrials = trials;
+    }
+
+    /**
+     * Access the number of trials for this distribution.
+     *
+     * @return the number of trials.
+     */
+    public int getNumberOfTrials() {
+        return numberOfTrials;
+    }
+
+    /**
+     * Access the probability of success for this distribution.
+     *
+     * @return the probability of success.
+     */
+    public double getProbabilityOfSuccess() {
+        return probabilityOfSuccess;
+    }
+
+    /** {@inheritDoc} */
+    public double probability(int x) {
+        final double logProbability = logProbability(x);
+        return logProbability == Double.NEGATIVE_INFINITY ? 0 : FastMath.exp(logProbability);
+    }
+
+    /** {@inheritDoc} * */
+    @Override
+    public double logProbability(int x) {
+        if (numberOfTrials == 0) {
+            return (x == 0) ? 0. : Double.NEGATIVE_INFINITY;
+        }
+        double ret;
+        if (x < 0 || x > numberOfTrials) {
+            ret = Double.NEGATIVE_INFINITY;
+        } else {
+            ret =
+                    SaddlePointExpansion.logBinomialProbability(
+                            x, numberOfTrials, probabilityOfSuccess, 1.0 - probabilityOfSuccess);
+        }
+        return ret;
+    }
+
+    /** {@inheritDoc} */
+    public double cumulativeProbability(int x) {
+        double ret;
+        if (x < 0) {
+            ret = 0.0;
+        } else if (x >= numberOfTrials) {
+            ret = 1.0;
+        } else {
+            ret = 1.0 - Beta.regularizedBeta(probabilityOfSuccess, x + 1.0, numberOfTrials - x);
+        }
+        return ret;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>For {@code n} trials and probability parameter {@code p}, the mean is {@code n * p}.
+     */
+    public double getNumericalMean() {
+        return numberOfTrials * probabilityOfSuccess;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>For {@code n} trials and probability parameter {@code p}, the variance is {@code n * p *
+     * (1 - p)}.
+     */
+    public double getNumericalVariance() {
+        final double p = probabilityOfSuccess;
+        return numberOfTrials * p * (1 - p);
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>The lower bound of the support is always 0 except for the probability parameter {@code p =
+     * 1}.
+     *
+     * @return lower bound of the support (0 or the number of trials)
+     */
+    public int getSupportLowerBound() {
+        return probabilityOfSuccess < 1.0 ? 0 : numberOfTrials;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>The upper bound of the support is the number of trials except for the probability
+     * parameter {@code p = 0}.
+     *
+     * @return upper bound of the support (number of trials or 0)
+     */
+    public int getSupportUpperBound() {
+        return probabilityOfSuccess > 0.0 ? numberOfTrials : 0;
+    }
+
+    /**
+     * {@inheritDoc}
+     *
+     * <p>The support of this distribution is connected.
+     *
+     * @return {@code true}
+     */
+    public boolean isSupportConnected() {
+        return true;
+    }
+}