public void Pimh_BayesPointMachine()
{
var posterior = BpmUpdate(BpmPrior, BpmObserved);
var samples = Samples(Pimh.Create(500, 50, posterior).SampleNParallel(100).SelectMany(d => d).SelectMany(d => d));
var approxPosterior = CategoricalF(samples.Normalize());
Debug.WriteLine(BpmPredict(approxPosterior, Person1));
Debug.WriteLine(BpmPredict(approxPosterior, Person2));
Debug.WriteLine(BpmPredict(approxPosterior, Person3));
}
public void Pimh_HiddenMarkov()
{
var hmmModel = Hmm(ObservedHmmData1);
var smcHmmSamples = Pimh.Create(100, 100, hmmModel).Sample();
var topSamples = Samples((from samples in smcHmmSamples
from sample in samples.Weights
select sample)
.GroupBy(ip => ShowLatentList(ip.Item))
.OrderByDescending(group => group.First().Prob.Value)
.Take(5).Select(g => g.First()));
Debug.WriteLine(Histogram.Finite(topSamples, ShowLatentList));
}
public void Pimh_LinReg()
{
var prior = from a in Normal(0, 100)
from b in Normal(0, 100)
select new Param(a, b);
var sandLinReg = CreateLinearRegression(prior, BeachSandData);
var pimhLinReg = Pimh.Create(100, 1000, sandLinReg).Sample();
var paramA = from samples in pimhLinReg
from aProb in samples.MapSample(param => param.a)
select aProb;
var paramB = from samples in pimhLinReg
from bProb in samples.MapSample(param => param.b)
select bProb;
Debug.WriteLine(Histogram.Weighted(paramA));
Debug.WriteLine(Histogram.Weighted(paramB));
}
public void Pimh_Dice()
{
// Exact posterior conditioned die
var twoRollsExact = Dice.ConditionalDieExact(2);
Debug.WriteLine(twoRollsExact.Histogram());
// Posterior inferred with SMC
var twoRolls = Dice.ConditionalDie(2);
var pimhPosterior = Pimh.Create(100, 1000, twoRolls).Sample();
var weights = from samples in pimhPosterior
from sample in samples
select sample;
var klDivergence = KullbackLeibler.KLDivergence(Samples(weights), twoRollsExact, d => d);
Debug.WriteLine($"KL divergence: {klDivergence}");
Assert.IsTrue(klDivergence < 0.5);
var doubleWeights = weights.Select(ip => ItemProb((double)ip.Item, ip.Prob));
Debug.WriteLine(Histogram.Weighted(doubleWeights, scale: 60));
}
