private static double BetaLn(double z, double w)
{
#if NONE
return(SpecialFunctions.BetaLn(z, w));
#else
return(Beta.BetaLn(z, w));
#endif
}
public void BetaLnFunctionForZeroSuccesses()
{
var delta = 0.05;
var prior = new EbisuModel(1.0, 34.4, 3.4);
var updatedModel = prior.UpdateRecall(0, 5, 0.1);
Assert.AreEqual(3.0652051705190964, updatedModel.Time, delta);
Assert.AreEqual(8.706432410647471, updatedModel.Beta, delta);
Assert.AreEqual(8.760308130181903, updatedModel.Alpha, delta);
#if NONE
double timeNow = 0.1;
double timeBack = prior.Time;
int successes = 0;
int total = 5;
double alpha = prior.Alpha;
double beta = prior.Beta;
double t = prior.Time;
double dt = timeNow / t;
double et = timeBack / timeNow;
var failures = total - successes;
var binomlns = Enumerable.Range(0, failures + 1)
.Select(i => BinomialLn(failures, i)).ToArray();
var logs1 =
Enumerable.Range(0, 3)
.Select(m =>
{
var a =
Enumerable.Range(0, failures + 1)
.Select(i => binomlns[i] + SpecialFunctions.BetaLn(
beta,
alpha + (dt * (successes + i)) + (m * dt * et)))
.ToList();
var b = Enumerable.Range(0, failures + 1)
.Select(i => Math.Pow(-1.0, i))
.ToList();
return(LogSumExp(a, b)[0]);
})
.ToArray();
var logs2 =
Enumerable.Range(0, 3)
.Select(m =>
{
var a =
Enumerable.Range(0, failures + 1)
.Select(i => binomlns[i] + Beta.BetaLn(
beta,
alpha + (dt * (successes + i)) + (m * dt * et)))
.ToList();
var b = Enumerable.Range(0, failures + 1)
.Select(i => Math.Pow(-1.0, i))
.ToList();
return(LogSumExp(a, b)[0]);
})
.ToArray();
for (int i = 0; i < logs1.Length; i++)
{
Assert.AreEqual(logs1[i], logs2[i], 1e-3);
}
#endif
}
