CDFIfc (JSLAll 1.0-SNAPSHOT API)

All Known Subinterfaces:

ContinuousDistributionIfc, DiscreteDistributionIfc, DistributionFunctionIfc, DistributionIfc, LossFunctionDistributionIfc

All Known Implementing Classes:

Bernoulli, Beta, Binomial, Constant, DEmpiricalCDF, Distribution, DUniform, Exponential, Gamma, Geometric, LogLogistic, Lognormal, MTP, NegativeBinomial, Normal, PearsonType5, PearsonType6, Poisson, ShiftedDistribution, ShiftedGeometric, ShiftedLossFunctionDistribution, StudentT, Triangular, TruncatedDistribution, Uniform, VConstant, Weibull
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public interface CDFIfc
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Provides an interface for functions related to a cumulative distribution function CDF

Method Summary

All Methods Instance Methods Abstract Methods Default Methods
Modifier and Type	Method	Description
`double`	`cdf(double x)`	Returns the F(x) = Pr{X <= x} where F represents the cumulative distribution function
`default double`	`cdf(double x1, double x2)`	Returns the Pr{x1<=X<=x2} for the distribution
`default double`	`complementaryCDF(double x)`	Computes the complementary cumulative probability distribution function for given value of x

- Method Detail
  - cdf
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double cdf(double x)
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    Returns the F(x) = Pr{X <= x} where F represents the cumulative distribution function
    
    Parameters:
    
    x - a double representing the upper limit
    
    Returns:
    
    a double representing the probability
  - cdf
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default double cdf(double x1,
                   double x2)
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    Returns the Pr{x1<=X<=x2} for the distribution
    
    Parameters:
    
    x1 - a double representing the lower limit
    
    x2 - a double representing the upper limit
    
    Returns:
    
    cdf(x2)-cdf(x1)
    
    Throws:
    
    java.lang.IllegalArgumentException - if x1 > x2
  - complementaryCDF
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default double complementaryCDF(double x)
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    Computes the complementary cumulative probability distribution function for given value of x
    
    Parameters:
    
    x - The value to be evaluated
    
    Returns:
    
    The probability, 1-P{X<=x}