private EmpiricalDistribution GetSimulatedDistribution(ISampleableDistribution <double> hypothesizedDistribution,
bool reestimate, int iterations, KolmogorovSmirnovTestHypothesis alternate)
{
double[] samples = new double[iterations];
if (reestimate)
{
Parallel.For(0, iterations, i =>
{
double[] s = hypothesizedDistribution.Generate(samples: NumberOfSamples);
Vector.Sort <double>(s);
var fittable = (IFittableDistribution <double>)hypothesizedDistribution.Clone();
fittable.Fit(s);
samples[i] = KolmogorovSmirnovTest.GetStatistic((double[])s, (IDistribution <double>)fittable, alternate);
});
}
else
{
Parallel.For(0, iterations, i =>
{
double[] s = hypothesizedDistribution.Generate(samples: NumberOfSamples);
Vector.Sort <double>(s);
samples[i] = KolmogorovSmirnovTest.GetStatistic((double[])s, (IDistribution <double>)hypothesizedDistribution, alternate);
});
}
return(new EmpiricalDistribution(samples, smoothing: 0));
}
/// <summary>
/// Creates a new One-Sample Lilliefors' Kolmogorov-Smirnov test.
/// </summary>
///
/// <param name="sample">The sample we would like to test as belonging to the <paramref name="hypothesizedDistribution"/>.</param>
/// <param name="hypothesizedDistribution">A fully specified distribution (which could have been estimated from the data).</param>
/// <param name="alternate">The alternative hypothesis (research hypothesis) to test.</param>
/// <param name="iterations">The number of Monte-Carlo iterations to perform. Default is 10,000.</param>
/// <param name="reestimate">Whether the target distribution should be re-estimated from the sampled data
/// at each Monte-Carlo iteration. Pass true in case <paramref name="hypothesizedDistribution"/> has been
/// estimated from the data.</param>
///
public LillieforsTest(double[] sample, ISampleableDistribution <double> hypothesizedDistribution,
KolmogorovSmirnovTestHypothesis alternate = KolmogorovSmirnovTestHypothesis.SampleIsDifferent,
int iterations = 10000, bool reestimate = true)
: this()
{
if (reestimate)
{
if (!(hypothesizedDistribution is IFittableDistribution <double>))
{
throw new InvalidOperationException("The estimate option can only be used with distributions that implement IFittableDistribution<double>.");
}
}
this.Hypothesis = alternate;
// Create a copy of the samples to prevent altering the
// constructor's original arguments in the sorting step
double[] orderedSamples = sample.Sorted();
// Create the theoretical and empirical distributions
this.TheoreticalDistribution = hypothesizedDistribution;
this.EmpiricalDistribution = new EmpiricalDistribution(orderedSamples, smoothing: 0);
this.NumberOfSamples = sample.Length;
StatisticDistribution = GetSimulatedDistribution(hypothesizedDistribution,
reestimate, iterations, alternate);
// Finally, compute the test statistic and perform actual testing.
base.Statistic = KolmogorovSmirnovTest.GetStatistic(orderedSamples, TheoreticalDistribution, alternate);
this.Tail = (DistributionTail)alternate;
base.PValue = StatisticToPValue(Statistic);
}
