Package | Description |
---|---|
org.drip.learning.rxtor1 | |
org.drip.sequence.custom | |
org.drip.sequence.functional |
Modifier and Type | Class and Description |
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class |
EmpiricalPenaltySupremumEstimator
EmpiricalPenaltySupremumEstimator contains the Implementation of the Empirical Penalty Supremum Estimator
dependent on Multivariate Random Variables where the Multivariate Function is a Linear Combination of
Bounded Univariate Functions acting on each Random Variate.
|
Modifier and Type | Class and Description |
---|---|
class |
GlivenkoCantelliFunctionSupremum
GlivenkoCantelliFunctionSupremum contains the Implementation of the Supremum Class Objective Function
dependent on Multivariate Random Variables where the Multivariate Function is a Linear Combination of Bounded
Univariate Functions acting on each Random Variate.
|
class |
GlivenkoCantelliUniformDeviation
GlivenkoCantelliUniformDeviation contains the Implementation of the Bounded Objective Function dependent
on Multivariate Random Variables where the Multivariate Function is a Linear Combination of Bounded
Univariate Functions acting on each Random Variate.
|
class |
KernelDensityEstimationL1
KernelDensityEstimationL1 implements the L1 Error Scheme Estimation for a Multivariate Kernel Density
Estimator with Focus on establishing targeted Variate-Specific and Agnostic Bounds.
|
class |
LongestCommonSubsequence
LongestCommonSubsequence contains Variance Bounds on the Critical Measures of the Longest Common
Subsequence between two Strings.
|
class |
OrientedPercolationFirstPassage
OrientedPercolationFirstPassage contains Variance Bounds on the Critical Measures of the Standard Problem
of First Passage Time in Oriented Percolation.
|
Modifier and Type | Class and Description |
---|---|
class |
BoundedMultivariateRandom
BoundedMultivariateRandom contains the Implementation of the Bounded Objective Function dependent on
Multivariate Random Variables.
|
class |
FlatMultivariateRandom
FlatMultivariateRandom contains the Implementation of the Flat Objective Function dependent on
Multivariate Random Variables.
|
Modifier and Type | Method and Description |
---|---|
SingleSequenceAgnosticMetrics[] |
EfronSteinMetrics.pivotedDifferenceSequenceMetrics(MultivariateRandom funcPivot)
Compute the Function Sequence Agnostic Metrics associated with each Variate around the Pivot Point
provided by the Pivot Function
|
double |
EfronSteinMetrics.pivotVarianceUpperBound(MultivariateRandom funcPivot)
Compute the Function Variance Upper Bound using the supplied Multivariate Pivoting Function
|
Constructor and Description |
---|
EfronSteinMetrics(MultivariateRandom func,
SingleSequenceAgnosticMetrics[] aSSAM)
EfronSteinMetrics Constructor
|