Numerical Linear Algebra with Applications · 2016 · 13 citations · 16 references
ComputingComputer ScienceFinanceComputational ElectromagneticsComputational MechanicsScientific ComputingMatrix ComputationMatrix FactorizationMatrix StructureMatrix SystemsNumerical AnalysisNumerical Linear AlgebraAccuracyComputational Matrix TheoryCorrelation MatrixEigenvalue AlgorithmsEigenvalue ComputationEigenvalue Extraction
Summary Schoenmakers–Coffey matrices are correlation matrices with important financial applications. Several characterizations of positive extended Schoenmakers–Coffey matrices are presented. This paper provides an accurate and fast method to obtain the bidiagonal decomposition of the conversion of these matrices, which in turn can be used to compute with high relative accuracy the eigenvalues and inverses of positive extended Schoenmakers–Coffey matrices. Numerical examples are included.
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T. Andô · Linear Algebra and its Applications · 1987 · 490 citations
Total positivity and Neville elimination
M. Gasca, J.M. Peña · Linear Algebra and its Applications · 1992 · 233 citations
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