本文整理了Java中org.apache.mahout.math.jet.random.Gamma.logGamma()方法的一些代码示例，展示了Gamma.logGamma()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Gamma.logGamma()方法的具体详情如下：
包路径：org.apache.mahout.math.jet.random.Gamma
类名称：Gamma
方法名：logGamma

Gamma.logGamma介绍

[英]Returns a quick approximation of log(gamma(x)).
[中]返回对数（gamma（x））的快速近似值。

代码示例

代码示例来源：origin: apache/mahout

/** Returns the probability distribution function.
 * @param x Where to compute the density function.
 *
 * @return The value of the gamma density at x.
 */
@Override
public double pdf(double x) {
 if (x < 0) {
  throw new IllegalArgumentException();
 }
 if (x == 0) {
  if (alpha == 1.0) {
   return rate;
  } else if (alpha < 1) {
   return Double.POSITIVE_INFINITY;
  } else {
   return 0;
  }
 }
 if (alpha == 1.0) {
  return rate * Math.exp(-x * rate);
 }
 return rate * Math.exp((alpha - 1.0) * Math.log(x * rate) - x * rate - logGamma(alpha));
}

代码示例来源：origin: cloudera/mahout

/** Returns the probability distribution function.
 * @param x Where to compute the density function.
 *
 * @return The value of the gamma density at x.
 */
@Override
public double pdf(double x) {
 if (x < 0) {
  throw new IllegalArgumentException();
 }
 if (x == 0) {
  if (alpha == 1.0) {
   return rate;
  } else if (alpha < 1) {
   return Double.POSITIVE_INFINITY;
  } else {
   return 0;
  }
 }
 if (alpha == 1.0) {
  return rate * Math.exp(-x * rate);
 }
 return rate * Math.exp((alpha - 1.0) * Math.log(x * rate) - x * rate - logGamma(alpha));
}

代码示例来源：origin: org.apache.mahout/mahout-math

/** Returns the probability distribution function.
 * @param x Where to compute the density function.
 *
 * @return The value of the gamma density at x.
 */
@Override
public double pdf(double x) {
 if (x < 0) {
  throw new IllegalArgumentException();
 }
 if (x == 0) {
  if (alpha == 1.0) {
   return rate;
  } else if (alpha < 1) {
   return Double.POSITIVE_INFINITY;
  } else {
   return 0;
  }
 }
 if (alpha == 1.0) {
  return rate * Math.exp(-x * rate);
 }
 return rate * Math.exp((alpha - 1.0) * Math.log(x * rate) - x * rate - logGamma(alpha));
}