public TransformedDistribution(Distribution baseDistribution, double shift, double scale)
{
if (baseDistribution == null) throw new ArgumentNullException("baseDistribution");
this.baseDistribution = baseDistribution;
this.shift = shift;
this.scale = scale;
}
public static Sample CreateSample(Distribution distribution, int count, int seed)
{
Sample sample = new Sample();
Random rng = new Random(seed);
for (int i = 0; i < count; i++) {
double x = distribution.GetRandomValue(rng);
sample.Add(x);
}
return (sample);
}
private void DistributionProbabilityTestHelper(Distribution distribution, double x)
{
Console.WriteLine("{0} {1}", distribution.GetType().Name, x);
double P = distribution.LeftProbability(x);
double Q = distribution.RightProbability(x);
Console.WriteLine(" P={0} Q={1} P+Q={2}", P, Q, P + Q);
Assert.IsTrue((0.0 <= P) && (P <= 1.0));
Assert.IsTrue((0.0 <= Q) && (Q <= 1.0));
Assert.IsTrue(TestUtilities.IsNearlyEqual(P + Q, 1.0));
// this is a rather poor test; we can do much more when we get integration
// update: we have integration now, and tests like DistributionUnitarityIntegralTest,
// DistributionMeanIntegralTest, DistributionVarianceIntegralTest, DistributionRawMomentIntegralTest,
// and DistributionCentralMomentIntegralTest use it
double p = distribution.ProbabilityDensity(x);
Console.WriteLine(" p={0}", p);
Assert.IsTrue(p >= 0.0);
}
private static Sample CreateSample(Distribution distribution, int count)
{
return (CreateSample(distribution, count, 1));
}
public void TestMoments(Distribution d)
{
// the support gives the limits of integration
Interval support = d.Support;
// raw moments
double[] M = new double[6];
for (int n = 0; n < 6; n++) {
// define x^n p(x)
Func<double, double> raw = delegate(double x) {
return (Math.Pow(x, n) * d.ProbabilityDensity(x));
};
// integrate it
M[n] = FunctionMath.Integrate(raw, support);
// compare with the claimed result
Console.WriteLine("M{0} {1} v. {2}", n, M[n], d.Moment(n));
}
// central moments
double[] C = new double[6];
for (int n = 0; n < 6; n++) {
// define (x-m)^n p(x)
Func<double, double> central = delegate(double x) {
return (Math.Pow(x - M[1], n) * d.ProbabilityDensity(x));
};
// integrate it
C[n] = FunctionMath.Integrate(central, support);
// compare with the claimed result
Console.WriteLine("C{0} {1} v. {2}", n, C[n], d.MomentAboutMean(n));
}
Console.WriteLine("Mean {0} v. {1}", M[1], d.Mean);
Console.WriteLine("Standard Deviation {0} v. {1}", Math.Sqrt(C[2]), d.StandardDeviation);
}
internal TestResult(double statistic, Distribution distribution)
{
this.statistic = statistic;
this.distribution = distribution;
}
