Package org.drip.spaces.metric
Interface RdNormed
- All Superinterfaces:
GeneralizedMetricVectorSpace
,GeneralizedVector
,RdGeneralizedVector
- All Known Implementing Classes:
RdCombinatorialBall
,RdCombinatorialBanach
,RdCombinatorialHilbert
,RdContinuousBall
,RdContinuousBanach
,RdContinuousHilbert
public interface RdNormed extends GeneralizedMetricVectorSpace, RdGeneralizedVector
RdNormed Abstract Class implements the Normed, Bounded/Unbounded Continuous/Combinatorial
lp Rd Spaces.
- Carl, B., and I. Stephani (1990): Entropy, Compactness, and the Approximation of Operators Cambridge University Press Cambridge UK
- Module = Computational Core Module
- Library = Statistical Learning Library
- Project = R1 and Rd Vector/Tensor Spaces (Validated and/or Normed), and Function Classes
- Package = Hilbert/Banach Normed Metric Spaces
- Author:
- Lakshmi Krishnamurthy
-
Method Summary
Modifier and Type Method Description double
borelMeasureSpaceExpectation(RdToR1 funcRdToR1)
Compute the Borel Measure Expectation for the specified R^d To R^1 Function over the full Input SpaceRd
borelSigmaMeasure()
Retrieve the Borel Sigma R^d Probability Measuredouble[]
populationMode()
Retrieve the Population Modedouble
populationSupremumNorm()
Compute the Population Supremum Norm of the Sampledouble
sampleMetricNorm(double[] adblX)
Compute the Metric Norm of the Sampledouble
sampleSupremumNorm(double[] adblX)
Compute the Supremum Norm of the SampleMethods inherited from interface org.drip.spaces.metric.GeneralizedMetricVectorSpace
pNorm, populationMetricNorm
Methods inherited from interface org.drip.spaces.tensor.GeneralizedVector
cardinality, hyperVolume, isPredictorBounded, leftEdge, match, rightEdge, subset
Methods inherited from interface org.drip.spaces.tensor.RdGeneralizedVector
dimension, leftDimensionEdge, rightDimensionEdge, validateInstance, vectorSpaces
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Method Details
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borelSigmaMeasure
Rd borelSigmaMeasure()Retrieve the Borel Sigma R^d Probability Measure- Returns:
- The Borel Sigma R^d Probability Measure
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sampleSupremumNorm
double sampleSupremumNorm(double[] adblX) throws java.lang.ExceptionCompute the Supremum Norm of the Sample- Parameters:
adblX
- The Sample- Returns:
- The Supremum Norm of the Sample
- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
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sampleMetricNorm
double sampleMetricNorm(double[] adblX) throws java.lang.ExceptionCompute the Metric Norm of the Sample- Parameters:
adblX
- The Sample- Returns:
- The Metric Norm of the Sample
- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
populationMode
double[] populationMode()Retrieve the Population Mode- Returns:
- The Population Mode
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populationSupremumNorm
double populationSupremumNorm() throws java.lang.ExceptionCompute the Population Supremum Norm of the Sample- Returns:
- The Population Supremum Norm of the Sample
- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
borelMeasureSpaceExpectation
Compute the Borel Measure Expectation for the specified R^d To R^1 Function over the full Input Space- Parameters:
funcRdToR1
- R^d To R^1 Function- Returns:
- The Borel Measure Expectation for the specified R^d To R^1 Function over the full Input Space
- Throws:
java.lang.Exception
- Thrown if the Population Mode cannot be calculated
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