public Markov <T> ToDistribution()
{
var initial = _initial.ToDistribution();
var transitions = _transitions.ToDictionary(
kv => kv.Key,
kv => kv.Value.ToDistribution());
IDistribution <T> Transition(T state) => transitions.GetValueOrDefault(state, Empty <T> .Distribution());
return(Markov <T> .Distribution(initial, Transition));
}
public static Metropolis <T> Distribution(
Func <T, float> target,
IDistribution <T> initial,
Func <T, IDistribution <T> > proposal,
IRNG random)
{
var markov = Markov <T> .Distribution(initial, Transition);
var chain = markov.Sample(random);
return(new Metropolis <T>(target, chain.GetEnumerator()));
IDistribution <T> Transition(T item)
{
T candidate = proposal(item).Sample(random);
float probability = target(candidate) / target(candidate);
return(Flip <T> .Distribution(candidate, item, probability));
}
}
