public class UniformRealDistribution extends AbstractRealDistribution
DEFAULT_SOLVER_ABSOLUTE_ACCURACY| Constructor and Description | 
|---|
| UniformRealDistribution()Create a standard uniform real distribution with lower bound (inclusive)
 equal to zero and upper bound (exclusive) equal to one. | 
| UniformRealDistribution(double lower,
                       double upper)Create a uniform real distribution using the given lower and upper
 bounds. | 
| Modifier and Type | Method and Description | 
|---|---|
| double | cumulativeProbability(double x)For a random variable  Xwhose values are distributed according
 to this distribution, this method returnsP(X <= x). | 
| double | density(double x)Returns the probability density function (PDF) of this distribution
 evaluated at the specified point  x. | 
| double | getNumericalMean()Use this method to get the numerical value of the mean of this
 distribution. | 
| double | getNumericalVariance()Use this method to get the numerical value of the variance of this
 distribution. | 
| double | getSupportLowerBound()Access the lower bound of the support. | 
| double | getSupportUpperBound()Access the upper bound of the support. | 
| double | inverseCumulativeProbability(double p)Computes the quantile function of this distribution. | 
| boolean | isSupportConnected()Use this method to get information about whether the support is connected,
 i.e. | 
getSolverAbsoluteAccuracy, logDensity, probabilitypublic UniformRealDistribution()
public UniformRealDistribution(double lower,
                               double upper)
                        throws MathIllegalArgumentException
lower - Lower bound of this distribution (inclusive).upper - Upper bound of this distribution (exclusive).MathIllegalArgumentException - if lower >= upper.public double density(double x)
x. In general, the PDF is
 the derivative of the CDF.
 If the derivative does not exist at x, then an appropriate
 replacement should be returned, e.g. Double.POSITIVE_INFINITY,
 Double.NaN, or  the limit inferior or limit superior of the
 difference quotient.x - the point at which the PDF is evaluatedxpublic double cumulativeProbability(double x)
X whose values are distributed according
 to this distribution, this method returns P(X <= x). In other
 words, this method represents the (cumulative) distribution function
 (CDF) for this distribution.x - the point at which the CDF is evaluatedxpublic double inverseCumulativeProbability(double p)
                                    throws MathIllegalArgumentException
X distributed according to this distribution, the
 returned value is
 inf{x in R | P(X<=x) >= p} for 0 < p <= 1,inf{x in R | P(X<=x) > 0} for p = 0.RealDistribution.getSupportLowerBound() for p = 0,RealDistribution.getSupportUpperBound() for p = 1.inverseCumulativeProbability in interface RealDistributioninverseCumulativeProbability in class AbstractRealDistributionp - the cumulative probabilityp-quantile of this distribution
 (largest 0-quantile for p = 0)MathIllegalArgumentException - if p < 0 or p > 1public double getNumericalMean()
lower and upper bound upper, the mean is
 0.5 * (lower + upper).Double.NaN if it is not definedpublic double getNumericalVariance()
lower and upper bound upper, the
 variance is (upper - lower)^2 / 12.Double.POSITIVE_INFINITY as
 for certain cases in TDistribution)
 or Double.NaN if it is not definedpublic double getSupportLowerBound()
inverseCumulativeProbability(0). In other words, this
 method must return
 inf {x in R | P(X <= x) > 0}.
public double getSupportUpperBound()
inverseCumulativeProbability(1). In other words, this
 method must return
 inf {x in R | P(X <= x) = 1}.
public boolean isSupportConnected()
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