public class LogisticDistribution extends AbstractRealDistribution
random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY| Constructor and Description | 
|---|
| LogisticDistribution(double mu,
                    double s)Build a new instance. | 
| LogisticDistribution(RandomGenerator rng,
                    double mu,
                    double s)Build a new instance. | 
| 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 | getLocation()Access the location parameter,  mu. | 
| 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 | getScale()Access the scale parameter,  s. | 
| 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. | 
| boolean | isSupportLowerBoundInclusive()Whether or not the lower bound of support is in the domain of the density
 function. | 
| boolean | isSupportUpperBoundInclusive()Whether or not the upper bound of support is in the domain of the density
 function. | 
cumulativeProbability, getSolverAbsoluteAccuracy, logDensity, probability, probability, reseedRandomGenerator, sample, samplepublic LogisticDistribution(double mu,
                    double s)
 Note: this constructor will implicitly create an instance of
 Well19937c as random generator to be used for sampling only (see
 AbstractRealDistribution.sample() and AbstractRealDistribution.sample(int)). In case no sampling is
 needed for the created distribution, it is advised to pass null
 as random generator via the appropriate constructors to avoid the
 additional initialisation overhead.
mu - location parameters - scale parameter (must be positive)NotStrictlyPositiveException - if beta <= 0public LogisticDistribution(RandomGenerator rng, double mu, double s)
rng - Random number generatormu - location parameters - scale parameter (must be positive)NotStrictlyPositiveException - if beta <= 0public double getLocation()
mu.public double getScale()
s.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 OutOfRangeException
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)OutOfRangeException - if p < 0 or p > 1public double getNumericalMean()
Double.NaN if it is not definedpublic double getNumericalVariance()
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}.
Double.NEGATIVE_INFINITY)public double getSupportUpperBound()
inverseCumulativeProbability(1). In other words, this
 method must return
 inf {x in R | P(X <= x) = 1}.
Double.POSITIVE_INFINITY)public boolean isSupportLowerBoundInclusive()
getSupporLowerBound() is finite and
 density(getSupportLowerBound()) returns a non-NaN, non-infinite
 value.public boolean isSupportUpperBoundInclusive()
getSupportUpperBound() is finite and
 density(getSupportUpperBound()) returns a non-NaN, non-infinite
 value.public boolean isSupportConnected()
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