Package org.apache.commons.math.distribution

Class WeibullDistributionImpl

java.lang.Object
org.apache.commons.math.distribution.AbstractDistribution
org.apache.commons.math.distribution.AbstractContinuousDistribution
org.apache.commons.math.distribution.WeibullDistributionImpl
All Implemented Interfaces:
Serializable, ContinuousDistribution, Distribution, WeibullDistribution
public class WeibullDistributionImpl extends AbstractContinuousDistribution implements WeibullDistribution, Serializable
Default implementation of WeibullDistribution.
Since:
1.1
Version:
$Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
See Also:

  • Field Details

    • DEFAULT_INVERSE_ABSOLUTE_ACCURACY

      public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
      Default inverse cumulative probability accuracy
      Since:
      2.1
      See Also:

  • Constructor Details

    • WeibullDistributionImpl

      public WeibullDistributionImpl(double alpha, double beta)
      Creates weibull distribution with the given shape and scale and a location equal to zero.
      Parameters:
      alpha - the shape parameter.
      beta - the scale parameter.

    • WeibullDistributionImpl

      public WeibullDistributionImpl(double alpha, double beta, double inverseCumAccuracy)
      Creates weibull distribution with the given shape, scale and inverse cumulative probability accuracy and a location equal to zero.
      Parameters:
      alpha - the shape parameter.
      beta - the scale parameter.
      inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates (defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)
      Since:
      2.1

  • Method Details

    • cumulativeProbability

      public double cumulativeProbability(double x)
      For this distribution, X, this method returns P(X < x).
      Specified by:
      cumulativeProbability in interface Distribution
      Parameters:
      x - the value at which the CDF is evaluated.
      Returns:
      CDF evaluated at x.

    • getShape

      public double getShape()
      Access the shape parameter.
      Specified by:
      getShape in interface WeibullDistribution
      Returns:
      the shape parameter.

    • getScale

      public double getScale()
      Access the scale parameter.
      Specified by:
      getScale in interface WeibullDistribution
      Returns:
      the scale parameter.

    • density

      public double density(double x)
      Returns the probability density for a particular point.
      Overrides:
      density in class AbstractContinuousDistribution
      Parameters:
      x - The point at which the density should be computed.
      Returns:
      The pdf at point x.
      Since:
      2.1

    • inverseCumulativeProbability

      public double inverseCumulativeProbability(double p)
      For this distribution, X, this method returns the critical point x, such that P(X < x) = p.

      Returns Double.NEGATIVE_INFINITY for p=0 and Double.POSITIVE_INFINITY for p=1.

      Specified by:
      inverseCumulativeProbability in interface ContinuousDistribution
      Overrides:
      inverseCumulativeProbability in class AbstractContinuousDistribution
      Parameters:
      p - the desired probability
      Returns:
      x, such that P(X < x) = p
      Throws:
      IllegalArgumentException - if p is not a valid probability.

    • setShape

      @Deprecated public void setShape(double alpha)
      Deprecated.
      as of 2.1 (class will become immutable in 3.0)
      Modify the shape parameter.
      Specified by:
      setShape in interface WeibullDistribution
      Parameters:
      alpha - the new shape parameter value.

    • setScale

      @Deprecated public void setScale(double beta)
      Deprecated.
      as of 2.1 (class will become immutable in 3.0)
      Modify the scale parameter.
      Specified by:
      setScale in interface WeibullDistribution
      Parameters:
      beta - the new scale parameter value.

    • getDomainLowerBound

      protected double getDomainLowerBound(double p)
      Access the domain value lower bound, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.
      Specified by:
      getDomainLowerBound in class AbstractContinuousDistribution
      Parameters:
      p - the desired probability for the critical value
      Returns:
      domain value lower bound, i.e. P(X < lower bound) < p

    • getDomainUpperBound

      protected double getDomainUpperBound(double p)
      Access the domain value upper bound, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.
      Specified by:
      getDomainUpperBound in class AbstractContinuousDistribution
      Parameters:
      p - the desired probability for the critical value
      Returns:
      domain value upper bound, i.e. P(X < upper bound) > p

    • getInitialDomain

      protected double getInitialDomain(double p)
      Access the initial domain value, based on p, used to bracket a CDF root. This method is used by inverseCumulativeProbability(double) to find critical values.
      Specified by:
      getInitialDomain in class AbstractContinuousDistribution
      Parameters:
      p - the desired probability for the critical value
      Returns:
      initial domain value

    • getSolverAbsoluteAccuracy

      protected double getSolverAbsoluteAccuracy()
      Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.
      Overrides:
      getSolverAbsoluteAccuracy in class AbstractContinuousDistribution
      Returns:
      the solver absolute accuracy
      Since:
      2.1

    • getSupportLowerBound

      public double getSupportLowerBound()
      Returns the lower bound of the support for the distribution. The lower bound of the support is always 0 no matter the parameters.
      Returns:
      lower bound of the support (always 0)
      Since:
      2.2

    • getSupportUpperBound

      public double getSupportUpperBound()
      Returns the upper bound of the support for the distribution. The upper bound of the support is always positive infinity no matter the parameters.
      Returns:
      upper bound of the support (always Double.POSITIVE_INFINITY)
      Since:
      2.2

    • calculateNumericalMean

      protected double calculateNumericalMean()
      Calculates the mean. The mean is scale * Gamma(1 + (1 / shape)) where Gamma(...) is the Gamma-function
      Returns:
      the mean
      Since:
      2.2

    • getNumericalMean

      public double getNumericalMean()
      Returns the mean of the distribution.
      Returns:
      the mean or Double.NaN if it's not defined
      Since:
      2.2

    • getNumericalVariance

      public double getNumericalVariance()
      Returns the variance of the distribution.
      Returns:
      the variance (possibly Double.POSITIVE_INFINITY as for certain cases in TDistributionImpl) or Double.NaN if it's not defined
      Since:
      2.2