Package org.drip.numerical.matrixnorm
Class R1SquareEvaluator
java.lang.Object
org.drip.numerical.matrixnorm.R1SquareEvaluator
- Direct Known Subclasses:
DoubleVectorNormEvaluator
,EntryWiseEvaluator
,SingleVectorNormEvaluator
public abstract class R1SquareEvaluator
extends java.lang.Object
R1SquareEvaluator exposes the Norm of a R1Square Matrix. The References are:
- Alon, N., and A. Naor (2004): Approximating the Cut-norm via Grothendieck Inequality Proceedings of the 36th Annual ACM Symposium on Theory of Computing STOC’04 ACM Chicago IL
- Golub, G. H., and C. F. van Loan (1996): Matrix Computations 3rd Edition Johns Hopkins University Press Baltimore MD
- Horn, R. A., and C. R. Johnson (2013): Matrix Analysis 2nd Edition Cambridge University Press Cambridge UK
- Lazslo, L. (2012): Large Networks and Graph Limits American Mathematical Society Providence RI
- Wikipedia (2024): Matrix Norm https://en.wikipedia.org/wiki/Matrix_norm
- Module = Computational Core Module
- Library = Numerical Analysis Library
- Project = Numerical Quadrature, Differentiation, Eigenization, Linear Algebra, and Utilities
- Package = Implementation of Matrix Norm Variants
- Author:
- Lakshmi Krishnamurthy
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Constructor Summary
Constructors Constructor Description R1SquareEvaluator()
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Method Summary
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Constructor Details
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R1SquareEvaluator
public R1SquareEvaluator()
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Method Details
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norm
Compute the Norm of the R1Square Matrix- Parameters:
r1Square
- R1Square Matrix- Returns:
- Norm of the R1Square Matrix
- Throws:
java.lang.Exception
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validator
public R1SquareConsistencyValidator validator(R1Square a, R1Square b, double[] v, double alpha, int p)Construct a Norm Consistency Validator for the Suite of Inputs- Parameters:
a
- Matrix Ab
- Matrix Bv
- Vector Valpha
- Alpha Scalep
- Vector Norm Index- Returns:
- The Norm Consistency Validator
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