Generating random correlation matrices with fixed values: an application to the evaluation of multivariate surrogate endpoints

DOI10.1016/j.csda.2019.106834OpenAlexW2971822027WikidataQ127307239 ScholiaQ127307239MaRDI QIDQ2008126

Geert Molenberghs, Ariel Alonso Abad, Alvaro Jóse Flórez, Wim Van Der Elst

Publication date: 22 November 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/643991

zbMATH Keywords

partial correlationrandom correlation matricespositive-definite matrixmultiple surrogate evaluationsimulation-based sensitivity analysis

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Measures of association (correlation, canonical correlation, etc.) (62H20) Positive matrices and their generalizations; cones of matrices (15B48) Random matrices (algebraic aspects) (15B52)

Related Items

An efficient algorithm to assess multivariate surrogate endpoints in a causal inference framework, Bayesian ridge regression for survival data based on a vine copula-based prior

Uses Software

• R
• SAS
• Surrogate

Cites Work

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