BinomialDistribution.java
/*
* Java Genetic Algorithm Library (@__identifier__@).
* Copyright (c) @__year__@ Franz Wilhelmstötter
*
* Licensed 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.
*
* Author:
* Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
*/
package org.jenetics.stat;
import static java.lang.String.format;
import static java.util.Objects.requireNonNull;
import static org.jenetics.internal.util.object.checkProbability;
import java.io.Serializable;
import org.jenetics.util.Function;
import org.jenetics.util.Range;
/**
* TODO: implement BinomialDistribution
*
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
* @since 1.0
* @version 2.0 — <em>$Date: 2014-03-12 $</em>
*/
class BinomialDistribution<
N extends Number & Comparable<? super N>
>
implements Distribution<N>
{
static final class PDF<N extends Number & Comparable<? super N>>
implements
Function<N, Double>,
Serializable
{
private static final long serialVersionUID = 2L;
private final Range<N> _domain;
private final long _N;
private final double _p;
private final double _q;
public PDF(final Range<N> domain, final double p) {
_domain = domain;
_N = domain.getMax().longValue() - domain.getMin().longValue();
_p = p;
_q = 1.0 - p;
}
@Override
public Double apply(final N value) {
final long x = value.longValue() - _domain.getMin().longValue();
double result = 0.0;
if (_domain.contains(value)) {
result = binomial(_N, x)*Math.pow(_p, x)*Math.pow(_q, _N - x);
}
return result;
}
@Override
public String toString() {
return format("p(x) = %s", "");
}
}
static final class CDF<N extends Number & Comparable<? super N>>
implements
Function<N, Double>,
Serializable
{
private static final long serialVersionUID = 2L;
private final Range<N> _domain;
private final long _N;
private final double _p;
private final double _q;
public CDF(final Range<N> domain, final double p) {
_domain = domain;
_N = domain.getMax().longValue() - domain.getMin().longValue();
_p = p;
_q = 1.0 - p;
}
@Override
public Double apply(final N value) {
long x = value.longValue();
double result = 0.0;
if (_domain.getMin().longValue() > x) {
result = 0.0;
} else if (_domain.getMax().longValue() < x) {
result = 1.0;
} else {
x = x - _domain.getMin().longValue();
double v = 0;
for (long i = 0; i <= x; ++i) {
v += binomial(_N, i)*Math.pow(_p, i)*Math.pow(_q, _N - i);
}
result = v;
}
return result;
}
@Override
public String toString() {
return format("p(x) = %s", "");
}
}
private final Range<N> _domain;
private final double _p;
public BinomialDistribution(final Range<N> domain, final double p) {
_domain = requireNonNull(domain, "Domain");
_p = checkProbability(p);
}
@Override
public Range<N> getDomain() {
return _domain;
}
@Override
public Function<N, Double> getCDF() {
return new CDF<>(_domain, _p);
}
@Override
public Function<N, Double> getPDF() {
return new PDF<>(_domain, _p);
}
private static double binomial(final long n, final long k) {
long b = 1;
for (long i = 1; i <= k; ++i) {
b *= (n - k + i)/i;
}
return b;
}
}