/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="IsGreaterThanOp"]/message_doc[@name="IsGreaterThanAverageConditional(int, Binomial)"]/*'/>
public static Bernoulli IsGreaterThanAverageConditional(int a, [Proper] Binomial b)
{
if (b.IsPointMass)
{
return(Bernoulli.PointMass(a > b.Point));
}
if (b.A == 1 && b.B == 1)
{
if (a <= 0)
{
return(Bernoulli.PointMass(false));
}
else if (a > b.TrialCount)
{
return(Bernoulli.PointMass(true));
}
else
{
return(new Bernoulli(MMath.Beta(1 - b.ProbSuccess, b.TrialCount - a + 1, a)));
}
}
else
{
double sum = 0;
for (int i = 0; i < a; i++)
{
sum += Math.Exp(b.GetLogProb(i));
}
if (sum > 1)
{
sum = 1; // this can happen due to round-off errors
}
return(new Bernoulli(sum));
}
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="IsGreaterThanOp"]/message_doc[@name="IsGreaterThanAverageConditional(Binomial, int)"]/*'/>
public static Bernoulli IsGreaterThanAverageConditional([Proper] Binomial a, int b)
{
if (a.IsPointMass)
{
return(Bernoulli.PointMass(a.Point > b));
}
if (a.A == 1 && a.B == 1)
{
if (b < 0)
{
return(Bernoulli.PointMass(true));
}
else if (b >= a.TrialCount)
{
return(Bernoulli.PointMass(false));
}
else
{
return(new Bernoulli(MMath.Beta(a.ProbSuccess, b + 1, a.TrialCount - b)));
}
}
else
{
double sum = 0;
for (int i = 0; i <= b; i++)
{
sum += Math.Exp(a.GetLogProb(i));
}
if (sum > 1)
{
sum = 1; // this can happen due to round-off errors
}
return(new Bernoulli(1 - sum));
}
}
/// <summary>
/// Compute the probability that a sample from this distribution is less than x.
/// </summary>
/// <param name="x">Any real number.</param>
/// <returns>The cumulative beta distribution at <paramref name="x"/></returns>
public double GetProbLessThan(double x)
{
if (x < 0.0)
{
return(0.0);
}
else if (x > 1.0)
{
return(1.0);
}
else if (this.IsPointMass)
{
return((this.Point < x) ? 1.0 : 0.0);
}
else if (this.IsUniform())
{
return(x);
}
else
{
return(MMath.Beta(x, this.TrueCount, this.FalseCount));
}
}
