public void TestMethod1()
{
Distribution n0 = new TransformedDistribution(new NormalDistribution(), -2.0, 3.0);
Distribution n1 = new NormalDistribution(-2.0, 3.0);
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.Mean, n1.Mean));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.Variance, n1.Variance));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.StandardDeviation, n1.StandardDeviation));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.Skewness, n1.Skewness));
for (int k = 0; k < 8; k++) {
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.Moment(k), n1.Moment(k)));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.MomentAboutMean(k), n1.MomentAboutMean(k)));
}
foreach (double x in TestUtilities.GenerateUniformRealValues(-8.0, 8.0, 8)) {
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.ProbabilityDensity(x), n1.ProbabilityDensity(x)));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.LeftProbability(x), n1.LeftProbability(x)));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.RightProbability(x), n1.RightProbability(x)));
}
foreach (double P in TestUtilities.GenerateRealValues(1.0E-4, 1.0, 4)) {
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.InverseLeftProbability(P), n1.InverseLeftProbability(P)));
Assert.IsTrue(TestUtilities.IsNearlyEqual(n0.InverseRightProbability(P), n1.InverseRightProbability(P)));
}
}
/*
* x: mide el tiempo
* y: mide la cantidad que ingresa en el anden
* m: es el máximo de la campana de gauss
* r1, r2: son números aleatorios
*/
public static int Normal(int minValue, int maxValue)
{
double r1, r2, m, x, y, mu, sigma, fx;
if ((minValue >= maxValue) || (minValue < 0) || (maxValue < 0))
{
throw new System.ArgumentException("Valores incorrectos");
}
mu = calcularMedia(minValue, maxValue);
sigma = calcularDesvio(minValue, maxValue);
NormalDistribution f = new NormalDistribution(mu, sigma);
m = 1 / (sigma * Math.Sqrt(2 * Math.PI));
do
{
r1 = Rand();
r2 = Rand();
x = minValue + (maxValue - minValue) * r1;
y = m * r2;
fx = f.ProbabilityDensity((x - mu) / sigma);
} while (y <= fx);
return Convert.ToInt32(x);
}