gov.sandia.cognition.statistics.distribution
Class StudentTDistribution.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.StudentTDistribution
                      extended by gov.sandia.cognition.statistics.distribution.StudentTDistribution.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,StudentTDistribution>, InvertibleCumulativeDistributionFunction<Double>, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateDistribution<Double>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
StudentTDistribution

public static class StudentTDistribution.CDF
extends StudentTDistribution
implements SmoothCumulativeDistributionFunction, InvertibleCumulativeDistributionFunction<Double>

Evaluator that computes the Cumulative Distribution Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom

See Also:
Serialized Form

Nested Class Summary
 
Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.StudentTDistribution
StudentTDistribution.CDF, StudentTDistribution.MaximumLikelihoodEstimator, StudentTDistribution.PDF, StudentTDistribution.WeightedMaximumLikelihoodEstimator
 
Field Summary
 
Fields inherited from class gov.sandia.cognition.statistics.distribution.StudentTDistribution
DEFAULT_DEGREES_OF_FREEDOM, DEFAULT_MEAN, DEFAULT_PRECISION, degreesOfFreedom, mean, precision
 
Constructor Summary
StudentTDistribution.CDF()
          Default constructor.
StudentTDistribution.CDF(double degreesOfFreedom)
          Creates a new instance of CDF
StudentTDistribution.CDF(double degreesOfFreedom, double mean, double precision)
          Creates a new instance of PDF
StudentTDistribution.CDF(StudentTDistribution other)
          Creates a new instance of CDF
 
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.
 double evaluateAsDouble(Double input)
          Evaluates the scalar function as a double.
 StudentTDistribution.CDF getCDF()
          Gets the CDF of a scalar distribution.
 StudentTDistribution.PDF getDerivative()
          Gets the closed-form derivative of the function.
 Double inverse(double p)
          Evaluates the Inverse Student-t CDF for the given probability and degrees of freedom
 
Methods inherited from class gov.sandia.cognition.statistics.distribution.StudentTDistribution
clone, convertFromVector, convertToVector, getDegreesOfFreedom, getEstimator, getMaxSupport, getMean, getMinSupport, getPrecision, getProbabilityFunction, getVariance, sample, setDegreesOfFreedom, setMean, setPrecision, toString
 
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

StudentTDistribution.CDF

public StudentTDistribution.CDF()
Default constructor.


StudentTDistribution.CDF

public StudentTDistribution.CDF(double degreesOfFreedom)
Creates a new instance of CDF

Parameters:
degreesOfFreedom - Degrees of freedom in the distribution, usually the number of datapoints - 1, DOFs must be greater than zero.

StudentTDistribution.CDF

public StudentTDistribution.CDF(double degreesOfFreedom,
                                double mean,
                                double precision)
Creates a new instance of PDF

Parameters:
degreesOfFreedom - Degrees of freedom in the distribution, usually the number of datapoints - 1, DOFs must be greater than zero.
mean - Mean, or noncentrality parameter, of the distribution
precision - Precision, inverseRootFinder variance, of the distribution, must be greater than zero.

StudentTDistribution.CDF

public StudentTDistribution.CDF(StudentTDistribution other)
Creates a new instance of CDF

Parameters:
other - The underlying Student t-distribution
Method Detail

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.

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

inverse

public Double inverse(double p)
Evaluates the Inverse Student-t CDF for the given probability and degrees of freedom

Specified by:
inverse in interface InvertibleCumulativeDistributionFunction<Double>
Parameters:
p - Value at which to solve for x such that x=CDF(p)
Returns:
Value of x such that x=CDF(p)

getCDF

public StudentTDistribution.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 StudentTDistribution
Returns:
CDF of the scalar distribution.

getDerivative

public StudentTDistribution.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