public override DNormal FromStat(ISuff s)
{
double mean = s.GetFirstMomentAsVector()[0];
double m2 = s.GetSecondMomentAsMatrix()[0, 0];
double variance = m2 - mean * mean;
return(new DNormal(mean, variance));
}
public override DBeta FromStat(ISuff s)
{
double mean = s.GetFirstMomentAsVector()[0];
double m2 = s.GetSecondMomentAsMatrix()[0, 0];
double variance = m2 - mean * mean;
Beta b = Beta.FromMeanAndVariance(mean, variance);
return(DBeta.FromBeta(b));
}
public override DGamma FromStat(ISuff s)
{
throw new NotImplementedException();
}
public override DNormal FromStat(ISuff s)
{
return(DNormalBuilder.Instance.FromStat(s));
}
// Get the sufficient statistic for the distribution.
// For example for a 1d Gaussian, the suff stat is [x; x.^2].
// The returned suff stat s is such that fromStat(s) gives back d.
//public abstract ISuff GetStat(T d);
// Construct a distribution from the sufficient statistics s.
public abstract T FromStat(ISuff s);