25 citations to https://www.mathnet.ru/eng/crmat2
  1. Michael Fleermann, Johannes Heiny, “Large sample covariance matrices of Gaussian observations with uniform correlation decay”, Stochastic Processes and their Applications, 162 (2023), 456  crossref
  2. Bryan T. Kelly, Semyon Malamud, Kangying Zhou, “The Virtue of Complexity in Return Prediction”, SSRN Journal, 2022  crossref
  3. Antoine Didisheim, Bryan T. Kelly, Semyon Malamud, “Deep Regression Ensembles”, SSRN Journal, 2022  crossref
  4. Alicja Dembczak-Kołodziejczyk, Anna Lytova, “On the empirical spectral distribution for certain models related to sample covariance matrices with different correlations”, Random Matrices: Theory Appl., 11:03 (2022)  crossref
  5. Yuichi Ikeda, Evolutionary Economics and Social Complexity Science, 28, Digital Designs for Money, Markets, and Social Dilemmas, 2022, 203  crossref
  6. Pavel Yaskov, “Limit of the smallest eigenvalue of a sample covariance matrix for spherical and related distributions”, Springer Proc. Math. Statist., 371 (2021), 229–241  mathnet  crossref  scopus
  7. Jennifer Bryson, Roman Vershynin, Hongkai Zhao, “Marchenko–Pastur law with relaxed independence conditions”, Random Matrices: Theory Appl., 10:04 (2021)  crossref
  8. Bryan T. Kelly, Semyon Malamud, “The Virtue of Complexity in Machine Learning Portfolios”, SSRN Journal, 2021  crossref
  9. G. L. Zitelli, “Random matrix models for datasets with fixed time horizons”, Quantitative Finance, 20:5 (2020), 769  crossref
  10. Fatih Yavuz ILGIN, “SIMO Haberleşme Kanallar{\i}nda Enerji Tabanlıİşbirlikli Spektrum Alg{\i}lama”, European Journal of Science and Technology, 2020, 96  crossref
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