gov.sandia.cognition.statistics.distribution
Class LogNormalDistribution.CDF

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.statistics.AbstractDistribution<NumberType>
          extended by gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<Double>
              extended by gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
                  extended by gov.sandia.cognition.statistics.distribution.LogNormalDistribution
                      extended by gov.sandia.cognition.statistics.distribution.LogNormalDistribution.CDF
All Implemented Interfaces:
Evaluator<Double,Double>, ClosedFormDifferentiableEvaluator<Double,Double,Double>, DifferentiableEvaluator<Double,Double,Double>, Vectorizable, ScalarFunction<Double>, UnivariateScalarFunction, ClosedFormComputableDistribution<Double>, ClosedFormCumulativeDistributionFunction<Double>, ClosedFormDistribution<Double>, ClosedFormUnivariateDistribution<Double>, ComputableDistribution<Double>, CumulativeDistributionFunction<Double>, Distribution<Double>, DistributionWithMean<Double>, EstimableDistribution<Double,LogNormalDistribution>, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateDistribution<Double>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
LogNormalDistribution

public static class LogNormalDistribution.CDF
extends LogNormalDistribution
implements SmoothCumulativeDistributionFunction

CDF of the Log-Normal Distribution

See Also:
Serialized Form

Nested Class Summary
 
Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
LogNormalDistribution.CDF, LogNormalDistribution.MaximumLikelihoodEstimator, LogNormalDistribution.PDF, LogNormalDistribution.WeightedMaximumLikelihoodEstimator
 
Field Summary
 
Fields inherited from class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
DEFAULT_LOG_NORMAL_MEAN, DEFAULT_LOG_NORMAL_VARIANCE, SQRT2PI
 
Constructor Summary
LogNormalDistribution.CDF()
          Default constructor.
LogNormalDistribution.CDF(double logNormalMean, double logNormalVariance)
          Creates a new instance of LogNormalDistribution
LogNormalDistribution.CDF(LogNormalDistribution other)
          Copy Constructor
 
Method Summary
 Double differentiate(Double input)
          Differentiates the output with respect to the input
 double evaluate(double input)
          Produces a double output for the given double input
 Double evaluate(Double input)
          Evaluates the function on the given input and returns the output.
static double evaluate(double x, double logNormalMean, double logNormalVariance)
          Evaluates the Log-Normal CDF for the given input and parameters
 double evaluateAsDouble(Double input)
          Evaluates the scalar function as a double.
 LogNormalDistribution.CDF getCDF()
          Gets the CDF of a scalar distribution.
 LogNormalDistribution.PDF getDerivative()
          Gets the closed-form derivative of the function.
 
Methods inherited from class gov.sandia.cognition.statistics.distribution.LogNormalDistribution
convertFromVector, convertToVector, getEstimator, getLogNormalMean, getLogNormalVariance, getMaxSupport, getMean, getMinSupport, getProbabilityFunction, getVariance, sample, setLogNormalMean, setLogNormalVariance, toString
 
Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution
clone
 
Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution
sample
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 
Methods inherited from interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution
getMean, getProbabilityFunction
 
Methods inherited from interface gov.sandia.cognition.statistics.UnivariateDistribution
getMaxSupport, getMinSupport, getVariance
 
Methods inherited from interface gov.sandia.cognition.statistics.Distribution
sample, sample
 
Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable
clone, convertFromVector, convertToVector
 

Constructor Detail

LogNormalDistribution.CDF

public LogNormalDistribution.CDF()
Default constructor.


LogNormalDistribution.CDF

public LogNormalDistribution.CDF(double logNormalMean,
                                 double logNormalVariance)
Creates a new instance of LogNormalDistribution

Parameters:
logNormalMean - Mean of the underlying distribution, (-infinity,+infinity)
logNormalVariance - Variance of the underlying distribution, (0,infinity)

LogNormalDistribution.CDF

public LogNormalDistribution.CDF(LogNormalDistribution other)
Copy Constructor

Parameters:
other - LogNormalDistribution to copy
Method Detail

evaluate

public double evaluate(double input)
Description copied from interface: UnivariateScalarFunction
Produces a double output for the given double input

Specified by:
evaluate in interface UnivariateScalarFunction
Parameters:
input - Input to the Evaluator
Returns:
output at the given input

evaluate

public static double evaluate(double x,
                              double logNormalMean,
                              double logNormalVariance)
Evaluates the Log-Normal CDF for the given input and parameters

Parameters:
x - Input about which to compute the CDF
logNormalMean - Mean of the underlying distribution, (-infinity,+infinity)
logNormalVariance - Variance of the underlying distribution, (0,infinity)
Returns:
CDF of the distribution

evaluate

public Double evaluate(Double input)
Description copied from interface: Evaluator
Evaluates the function on the given input and returns the output.

Specified by:
evaluate in interface Evaluator<Double,Double>
Parameters:
input - The input to evaluate.
Returns:
The output produced by evaluating the input.

evaluateAsDouble

public double evaluateAsDouble(Double input)
Description copied from interface: ScalarFunction
Evaluates the scalar function as a double.

Specified by:
evaluateAsDouble in interface ScalarFunction<Double>
Parameters:
input - The input value.
Returns:
The scalar output calculated from the given input.

getCDF

public LogNormalDistribution.CDF getCDF()
Description copied from interface: UnivariateDistribution
Gets the CDF of a scalar distribution.

Specified by:
getCDF in interface ClosedFormUnivariateDistribution<Double>
Specified by:
getCDF in interface SmoothUnivariateDistribution
Specified by:
getCDF in interface UnivariateDistribution<Double>
Overrides:
getCDF in class LogNormalDistribution
Returns:
CDF of the scalar distribution.

getDerivative

public LogNormalDistribution.PDF getDerivative()
Description copied from interface: ClosedFormDifferentiableEvaluator
Gets the closed-form derivative of the function.

Specified by:
getDerivative in interface ClosedFormDifferentiableEvaluator<Double,Double,Double>
Specified by:
getDerivative in interface SmoothCumulativeDistributionFunction
Returns:
Closed-form derivative of the function.

differentiate

public Double differentiate(Double input)
Description copied from interface: DifferentiableEvaluator
Differentiates the output with respect to the input

Specified by:
differentiate in interface DifferentiableEvaluator<Double,Double,Double>
Parameters:
input - Input about which to compute the derivative
Returns:
Derivative of the output with respect to the given input