Ilya Archakov, Peter Reinhard Hansen, Yiyao Luo
arXiv 15 Oct 2022 · Econometrics · publishedEconometrics Journal (2023) · 9 citations (OpenAlex)
arXiv:2210.08147 · PDF · DOI · OpenAlex · Extracted main text
We propose a new method for generating random correlation matrices that makes it simple to control both location and dispersion. The method is based on a vector parameterization, gamma = g(C), which maps any distribution on R^d, d = n(n-1)/2 to a distribution on the space of non-singular nxn correlation matrices. Correlation matrices with certain properties, such as being well-conditioned, having block structures, and having strictly positive elements, are simple to generate. We compare the new method with existing methods.
appendix boundary found by appendix_command · 79% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Archakov \ Hansen (2021) `A new parametrization of correlation matrices', Econometrica 89, 1699–1715 | 0.899 | 11 | 4 | 73% |
| 2 | Joe (2006) `Generating random correlation matrices based on partial correlations', Journal of Multivariate Analysis 97, 2177–2189 | 0.874 | 8 | 2 | 100% |
| 3 | Archakov \ Hansen (2022) `A canonical representation of block matrices with applications to covariance and correlation matrices', Forthcoming in Review o… | 0.644 | 4 | 2 | 50% |
| 4 | Marsaglia \ Olkin (1984) `Generating correlation matrices', SIAM Journal on Scientific Computing 5, 470–476 | 0.644 | 4 | 1 | 100% |
| 5 | Pourahmadi (2011) `Covariance estimation: The GLM and regularization perspectives', Statistical Science 26, 369–387 | 0.644 | 2 | 2 | 100% |
| 6 | Pourahmadi \ Wang (2015) `Distribution of random correlation matrices: Hyperspherical parameterization of the Cholesky factor', Statistics and Probabilit… | 0.644 | 2 | 2 | 100% |
| 7 | Archakov \ Hansen (2020) `A generalized Fisher transformation for correlation matrices: A simulation study of its finite sample properties', https://site… | 0.511 | 2 | 1 | 100% |
| 8 | Bendel \ Mickey (1978) `Population Correlation Matrices for Sampling Experiments', Communications in Statistics - Simulation and Computation 7, 163–182 | 0.511 | 2 | 1 | 100% |
| 9 | Chalmers (1975) `Generation of correlation matrices with a given eigen–structure', Journal of statistical computation and simulation 4, 133–139 | 0.511 | 2 | 1 | 100% |
| 10 | Davies \ Higham (2000) `Numerically stable generation of correlation matrices and their factors', BIT Numerical Mathematics 40, 640–651 | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 21 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Cluster GARCH | 0.405 | 1 | 1 |
| 2 | The Generalized Fisher Transformation: Finite-Sample Properties and Inference | 0.405 | 1 | 1 |
| 3 | A Multivariate Realized GARCH Model | 0.000 | 1 | 1 |