/// <inheritdoc/>
public new double logProbability(int x)
{
double ret;
int[] domain = getDomain(populationSize, numberOfSuccesses, sampleSize);
if (x < domain[0] || x > domain[1])
{
ret = Double.NegativeInfinity;
}
else
{
double p = (double)sampleSize / (double)populationSize;
double q = (double)(populationSize - sampleSize) / (double)populationSize;
double p1 = SaddlePointExpansion.logBinomialProbability(x,
numberOfSuccesses, p, q);
double p2 =
SaddlePointExpansion.logBinomialProbability(sampleSize - x,
populationSize - numberOfSuccesses, p, q);
double p3 =
SaddlePointExpansion.logBinomialProbability(sampleSize, populationSize, p, q);
ret = p1 + p2 - p3;
}
return(ret);
}
/// <inheritdoc/>
public new double logProbability(int x)
{
if (numberOfTrials == 0)
{
return((x == 0) ? 0d : Double.NegativeInfinity);
}
double ret;
if (x < 0 || x > numberOfTrials)
{
ret = Double.NegativeInfinity;
}
else
{
ret = SaddlePointExpansion.logBinomialProbability(x,
numberOfTrials, probabilityOfSuccess,
1.0 - probabilityOfSuccess);
}
return(ret);
}
/// <inheritdoc/>
public new double logProbability(int x)
{
double ret;
if (x < 0 || x == Int32.MaxValue)
{
ret = Double.NegativeInfinity;
}
else if (x == 0)
{
ret = -mean;
}
else
{
ret = -SaddlePointExpansion.getStirlingError(x) -
SaddlePointExpansion.getDeviancePart(x, mean) -
0.5 * FastMath.log(MathUtils.TWO_PI) - 0.5 * FastMath.log(x);
}
return(ret);
}
