public void TestContinuousDistributions_StudensT()
{
TestContinuousDistributionShapeMatchesCumulativeDensity(
new StudentsTDistribution(2),
-2.0, 5.0, 10, 100000, 0.01, "StudentsTDistribution(2)");
StudentsTDistribution d = new StudentsTDistribution(2);
// PDF - Evaluated in Maple with "stats[statevalf,pdf,studentst[2]](x);"
NumericAssert.AreAlmostEqual(0.3535533906, d.ProbabilityDensity(0.0), 1e-9, "pdf(0)");
NumericAssert.AreAlmostEqual(0.1924500897, d.ProbabilityDensity(1.0), 1e-9, "pdf(1)");
NumericAssert.AreAlmostEqual(0.06804138174, d.ProbabilityDensity(2.0), 1e-9, "pdf(2)");
NumericAssert.AreAlmostEqual(0.02741012223, d.ProbabilityDensity(3.0), 1e-9, "pdf(3)");
NumericAssert.AreAlmostEqual(0.01309457002, d.ProbabilityDensity(4.0), 1e-9, "pdf(4)");
NumericAssert.AreAlmostEqual(0.1924500897, d.ProbabilityDensity(-1.0), 1e-9, "pdf(-1)");
NumericAssert.AreAlmostEqual(0.06804138174, d.ProbabilityDensity(-2.0), 1e-9, "pdf(-2)");
NumericAssert.AreAlmostEqual(0.02741012223, d.ProbabilityDensity(-3.0), 1e-9, "pdf(-3)");
NumericAssert.AreAlmostEqual(0.01309457002, d.ProbabilityDensity(-4.0), 1e-9, "pdf(-4)");
// CDF - Evaluated in Maple with "stats[statevalf,cdf,studentst[2]](x);"
NumericAssert.AreAlmostEqual(0.5000000000, d.CumulativeDistribution(0.0), "cdf(0)");
NumericAssert.AreAlmostEqual(0.7886751346, d.CumulativeDistribution(1.0), 1e-9, "cdf(1)");
NumericAssert.AreAlmostEqual(0.9082482905, d.CumulativeDistribution(2.0), 1e-9, "cdf(2)");
NumericAssert.AreAlmostEqual(0.9522670169, d.CumulativeDistribution(3.0), 1e-9, "cdf(3)");
NumericAssert.AreAlmostEqual(0.9714045208, d.CumulativeDistribution(4.0), 1e-9, "cdf(4)");
NumericAssert.AreAlmostEqual(0.2113248654, d.CumulativeDistribution(-1.0), 1e-9, "cdf(-1)");
NumericAssert.AreAlmostEqual(0.09175170954, d.CumulativeDistribution(-2.0), 1e-9, "cdf(-2)");
NumericAssert.AreAlmostEqual(0.04773298313, d.CumulativeDistribution(-3.0), 1e-9, "cdf(-3)");
NumericAssert.AreAlmostEqual(0.02859547921, d.CumulativeDistribution(-4.0), 1e-9, "cdf(-4)");
}
//End of ui.cs file Contents
//-------------------------------------------------------------------------
//Begin of Random.cs file contents
/// <summary>
/// Initializes the random-number generator with a specific seed.
/// </summary>
public void Initialize(uint seed)
{
RandomNumberGenerator = new MT19937Generator(seed);
betaDist = new BetaDistribution(RandomNumberGenerator);
betaPrimeDist = new BetaPrimeDistribution(RandomNumberGenerator);
cauchyDist = new CauchyDistribution(RandomNumberGenerator);
chiDist = new ChiDistribution(RandomNumberGenerator);
chiSquareDist = new ChiSquareDistribution(RandomNumberGenerator);
continuousUniformDist = new ContinuousUniformDistribution(RandomNumberGenerator);
erlangDist = new ErlangDistribution(RandomNumberGenerator);
exponentialDist = new ExponentialDistribution(RandomNumberGenerator);
fisherSnedecorDist = new FisherSnedecorDistribution(RandomNumberGenerator);
fisherTippettDist = new FisherTippettDistribution(RandomNumberGenerator);
gammaDist = new GammaDistribution(RandomNumberGenerator);
laplaceDist = new LaplaceDistribution(RandomNumberGenerator);
lognormalDist = new LognormalDistribution(RandomNumberGenerator);
normalDist = new NormalDistribution(RandomNumberGenerator);
paretoDist = new ParetoDistribution(RandomNumberGenerator);
powerDist = new PowerDistribution(RandomNumberGenerator);
rayleighDist = new RayleighDistribution(RandomNumberGenerator);
studentsTDist = new StudentsTDistribution(RandomNumberGenerator);
triangularDist = new TriangularDistribution(RandomNumberGenerator);
weibullDist = new WeibullDistribution(RandomNumberGenerator);
poissonDist = new PoissonDistribution(RandomNumberGenerator);
// generator.randomGenerator = new MT19937Generator(seed);
}
static double TDIST(double x, int degrees_freedom, int tails)
{
StudentsTDistribution dist = new StudentsTDistribution(degrees_freedom);
switch (tails)
{
case 1:
return(1d - dist.CumulativeDistribution(x));
case 2:
return(1d - dist.CumulativeDistribution(x) + dist.CumulativeDistribution(-x));
default:
throw new ArgumentOutOfRangeException("tails");
}
}
/// <summary>
/// Sets the distribution for operations using the current genrator
/// </summary>
/// <param name="distx">Distx.</param>
public void setDistribution(distributions distx, Dictionary <string, double> args)
{
//TODO check arguments to ensure they are making a change to the distribution
//otherwise throw an exception see laplace as a example of implementing this
switch (distx)
{
case distributions.Bernoili:
BernoulliDistribution x0 = new BernoulliDistribution(gen);
if (args.ContainsKey("alpha"))
{
x0.Alpha = args["alpha"];
}
else
{
throw new System.Exception("for Bernoili distribution you must provide an alpha");
}
dist = x0;
break;
case distributions.Beta:
BetaDistribution x1 = new BetaDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x1.Alpha = args["alpha"];
x1.Beta = args["beta"];
}
else
{
throw new System.Exception(" for beta distribution you must provide alpha and beta");
}
dist = x1;
break;
case distributions.BetaPrime:
BetaPrimeDistribution x2 = new BetaPrimeDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x2.Alpha = args["alpha"];
x2.Beta = args["beta"];
}
else
{
throw new System.Exception(" for betaPrime distribution you must provide alpha and beta");
}
dist = x2;
break;
case distributions.Cauchy:
CauchyDistribution x3 = new CauchyDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("gamma"))
{
x3.Alpha = args["alpha"];
x3.Gamma = args["gamma"];
}
else
{
throw new System.Exception("for cauchy dist you must provide alpha and gamma");
}
dist = x3;
break;
case distributions.Chi:
ChiDistribution x4 = new ChiDistribution(gen);
if (args.ContainsKey("alpha"))
{
x4.Alpha = (int)args["alpha"];
}
else
{
throw new System.Exception("for chi you must provide alpha");
}
dist = x4;
break;
case distributions.ChiSquared:
ChiSquareDistribution x5 = new ChiSquareDistribution(gen);
if (args.ContainsKey("alpha"))
{
x5.Alpha = (int)args["alpha"];
}
else
{
throw new System.Exception("for chiSquared you must provide alpha");
}
dist = x5;
break;
case distributions.ContinuousUniform:
ContinuousUniformDistribution x6 = new ContinuousUniformDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x6.Alpha = args["alpha"];
x6.Beta = args["beta"];
}
else
{
throw new System.Exception("for ContinuousUniform you must provide alpha and beta");
}
dist = x6;
break;
case distributions.DiscreteUniform:
DiscreteUniformDistribution x7 = new DiscreteUniformDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x7.Alpha = (int)args["alpha"];
x7.Beta = (int)args["beta"];
}
else
{
throw new System.Exception("for discrete uniform distribution you must provide alpha and beta");
}
dist = x7;
break;
case distributions.Erlang:
ErlangDistribution x8 = new ErlangDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("lambda"))
{
x8.Alpha = (int)args["alpha"];
x8.Lambda = (int)args["lambda"];
}
else
{
throw new System.Exception("for Erlang dist you must provide alpha and lambda");
}
dist = x8;
break;
case distributions.Exponential:
ExponentialDistribution x9 = new ExponentialDistribution(gen);
if (args.ContainsKey("lambda"))
{
x9.Lambda = args["lambda"];
}
else
{
throw new System.Exception("for exponential dist you must provide lambda");
}
dist = x9;
break;
case distributions.FisherSnedecor:
FisherSnedecorDistribution x10 = new FisherSnedecorDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x10.Alpha = (int)args["alpha"];
x10.Beta = (int)args["beta"];
}
else
{
throw new System.Exception("for FisherSnedecor you must provide alpha and beta");
}
dist = x10;
break;
case distributions.FisherTippett:
FisherTippettDistribution x11 = new FisherTippettDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("mu"))
{
x11.Alpha = args["alpha"];
x11.Mu = args["mu"];
}
else
{
throw new System.Exception("for FisherTippets you must provide alpha and mu");
}
dist = x11;
break;
case distributions.Gamma:
GammaDistribution x12 = new GammaDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("theta"))
{
x12.Alpha = args["alpha"];
x12.Theta = args["theta"];
}
else
{
throw new System.Exception("for Gamma dist you must provide alpha and theta");
}
dist = x12;
break;
case distributions.Geometric:
GeometricDistribution x13 = new GeometricDistribution(gen);
if (args.ContainsKey("alpha"))
{
x13.Alpha = args["alpha"];
}
else
{
throw new System.Exception("Geometric distribution requires alpha value");
}
dist = x13;
break;
case distributions.Binomial:
BinomialDistribution x14 = new BinomialDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x14.Alpha = args["alpha"];
x14.Beta = (int)args["beta"];
}
else
{
throw new System.Exception("binomial distribution requires alpha and beta");
}
dist = x14;
break;
case distributions.None:
break;
case distributions.Laplace:
LaplaceDistribution x15 = new LaplaceDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("mu"))
{
if (x15.IsValidAlpha(args["alpha"]) && x15.IsValidMu(args["mu"]))
{
x15.Alpha = args["alpha"];
x15.Mu = args["mu"];
}
else
{
throw new ArgumentException("alpha must be greater than zero");
}
}
else
{
throw new System.Exception("Laplace dist requires alpha and mu");
}
dist = x15;
break;
case distributions.LogNormal:
LognormalDistribution x16 = new LognormalDistribution(gen);
if (args.ContainsKey("mu") && args.ContainsKey("sigma"))
{
x16.Mu = args["mu"];
x16.Sigma = args["sigma"];
}
else
{
throw new System.Exception("lognormal distribution requires mu and sigma");
}
dist = x16;
break;
case distributions.Normal:
NormalDistribution x17 = new NormalDistribution(gen);
if (args.ContainsKey("mu") && args.ContainsKey("sigma"))
{
x17.Mu = args["mu"];
x17.Sigma = args["sigma"];
}
else
{
throw new System.Exception("normal distribution requires mu and sigma");
}
dist = x17;
break;
case distributions.Pareto:
ParetoDistribution x18 = new ParetoDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x18.Alpha = args["alpha"];
x18.Beta = args["beta"];
}
else
{
throw new System.Exception("pareto distribution requires alpha and beta");
}
dist = x18;
break;
case distributions.Poisson:
PoissonDistribution x19 = new PoissonDistribution(gen);
if (args.ContainsKey("lambda"))
{
x19.Lambda = args["lambda"];
}
else
{
throw new System.Exception("Poisson distribution requires lambda");
}
dist = x19;
break;
case distributions.Power:
PowerDistribution x20 = new PowerDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta"))
{
x20.Alpha = args["alpha"];
x20.Beta = args["beta"];
}
else
{
throw new System.Exception("Power dist requires alpha and beta");
}
dist = x20;
break;
case distributions.RayLeigh:
RayleighDistribution x21 = new RayleighDistribution(gen);
if (args.ContainsKey("sigma"))
{
x21.Sigma = args["sigma"];
}
else
{
throw new System.Exception("Rayleigh dist requires sigma");
}
dist = x21;
break;
case distributions.StudentsT:
StudentsTDistribution x22 = new StudentsTDistribution(gen);
if (args.ContainsKey("nu"))
{
x22.Nu = (int)args["nu"];
}
else
{
throw new System.Exception("StudentsT dist requirres nu");
}
dist = x22;
break;
case distributions.Triangular:
TriangularDistribution x23 = new TriangularDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("beta") && args.ContainsKey("gamma"))
{
x23.Alpha = args["alpha"];
x23.Beta = args["beta"];
x23.Gamma = args["gamma"];
}
else
{
throw new System.Exception("Triangular distribution requires alpha, beta and gamma");
}
dist = x23;
break;
case distributions.WeiBull:
WeibullDistribution x24 = new WeibullDistribution(gen);
if (args.ContainsKey("alpha") && args.ContainsKey("lambda"))
{
x24.Alpha = args["alpha"];
x24.Lambda = args["lambda"];
}
else
{
throw new System.Exception("WeiBull dist requires alpha and lambda");
}
dist = x24;
break;
default:
throw new NotImplementedException("the distribution you want has not yet been implemented " +
"you could help everyone out by going and implementing it");
}
}
