Generating random correlation matrices based on partial correlations
AbstractA d-dimensional positive definite correlation matrix R=([rho]ij) can be parametrized in terms of the correlations [rho]i,i+1 for i=1,...,d-1, and the partial correlations [rho]iji+1,...j-1 for j-i[greater-or-equal, slanted]2. These parameters can independently take values in the interval (-1,1). Hence we can generate a random positive definite correlation matrix by choosing independent distributions Fij, 1[less-than-or-equals, slant]i
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 97 (2006)
Issue (Month): 10 (November)
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- Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2008.
"Control of the False Discovery Rate under Dependence using the Bootstrap and Subsampling,"
IEW - Working Papers
337, Institute for Empirical Research in Economics - University of Zurich.
- Joseph Romano & Azeem Shaikh & Michael Wolf, 2008. "Control of the false discovery rate under dependence using the bootstrap and subsampling," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 17(3), pages 417-442, November.
- Wang, Y. & Daniels, M.J., 2013. "Bayesian modeling of the dependence in longitudinal data via partial autocorrelations and marginal variances," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 130-140.
- Christopher J. Bennett, 2009. "p-Value Adjustments for Asymptotic Control of the Generalized Familywise Error Rate," Vanderbilt University Department of Economics Working Papers 0905, Vanderbilt University Department of Economics.
- Lewandowski, Daniel & Kurowicka, Dorota & Joe, Harry, 2009. "Generating random correlation matrices based on vines and extended onion method," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1989-2001, October.
- Daniels, M.J. & Pourahmadi, M., 2009. "Modeling covariance matrices via partial autocorrelations," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2352-2363, November.
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