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java.lang.Objectgov.sandia.cognition.util.AbstractCloneableSerializable
gov.sandia.cognition.statistics.AbstractDistribution<NumberType>
gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<Double>
gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution
gov.sandia.cognition.statistics.distribution.StudentTDistribution
gov.sandia.cognition.statistics.distribution.StudentTDistribution.PDF
public static class StudentTDistribution.PDF
Evaluator that computes the Probability Density Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom
Nested Class Summary |
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Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.StudentTDistribution |
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StudentTDistribution.CDF, StudentTDistribution.MaximumLikelihoodEstimator, StudentTDistribution.PDF, StudentTDistribution.WeightedMaximumLikelihoodEstimator |
Field Summary |
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Fields inherited from class gov.sandia.cognition.statistics.distribution.StudentTDistribution |
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DEFAULT_DEGREES_OF_FREEDOM, DEFAULT_MEAN, DEFAULT_PRECISION, degreesOfFreedom, mean, precision |
Constructor Summary | |
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StudentTDistribution.PDF()
Default constructor. |
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StudentTDistribution.PDF(double degreesOfFreedom)
Creates a new instance of PDF |
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StudentTDistribution.PDF(double degreesOfFreedom,
double mean,
double precision)
Creates a new instance of PDF |
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StudentTDistribution.PDF(StudentTDistribution other)
Creates a new instance of PDF |
Method Summary | |
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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.PDF |
getProbabilityFunction()
Gets the distribution function associated with this Distribution, either the PDF or PMF. |
double |
logEvaluate(double input)
Evaluate the natural logarithm of the distribution function. |
double |
logEvaluate(Double input)
Evaluate the natural logarithm of the distribution function. |
Methods inherited from class gov.sandia.cognition.statistics.distribution.StudentTDistribution |
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clone, convertFromVector, convertToVector, getCDF, getDegreesOfFreedom, getEstimator, getMaxSupport, getMean, getMinSupport, getPrecision, getVariance, sample, setDegreesOfFreedom, setMean, setPrecision, toString |
Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution |
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sample |
Methods inherited from class java.lang.Object |
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equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Methods inherited from interface gov.sandia.cognition.statistics.SmoothUnivariateDistribution |
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getCDF, getMean |
Methods inherited from interface gov.sandia.cognition.statistics.UnivariateDistribution |
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getMaxSupport, getMinSupport, getVariance |
Methods inherited from interface gov.sandia.cognition.statistics.Distribution |
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sample, sample |
Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable |
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clone, convertFromVector, convertToVector |
Constructor Detail |
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public StudentTDistribution.PDF()
public StudentTDistribution.PDF(double degreesOfFreedom)
degreesOfFreedom
- Degrees of freedom in the distribution, usually the number of
datapoints - 1, DOFs must be greater than zero.public StudentTDistribution.PDF(double degreesOfFreedom, double mean, double precision)
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 distributionprecision
- Precision, inverseRootFinder variance, of the distribution, must be greater
than zero.public StudentTDistribution.PDF(StudentTDistribution other)
other
- The underlying Student t-distributionMethod Detail |
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public Double evaluate(Double input)
Evaluator
evaluate
in interface Evaluator<Double,Double>
input
- The input to evaluate.
public double evaluateAsDouble(Double input)
ScalarFunction
evaluateAsDouble
in interface ScalarFunction<Double>
input
- The input value.
public double evaluate(double input)
UnivariateScalarFunction
evaluate
in interface UnivariateScalarFunction
input
- Input to the Evaluator
public double logEvaluate(Double input)
ProbabilityFunction
logEvaluate
in interface ProbabilityFunction<Double>
public double logEvaluate(double input)
UnivariateProbabilityDensityFunction
logEvaluate
in interface UnivariateProbabilityDensityFunction
input
- The input value.
public StudentTDistribution.PDF getProbabilityFunction()
ComputableDistribution
getProbabilityFunction
in interface ComputableDistribution<Double>
getProbabilityFunction
in interface ProbabilityDensityFunction<Double>
getProbabilityFunction
in interface SmoothUnivariateDistribution
getProbabilityFunction
in interface UnivariateProbabilityDensityFunction
getProbabilityFunction
in class StudentTDistribution
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