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Found 368 Documents (Results 1–100)

High-dimensional covariance matrix estimation. An introduction to random matrix theory. (English) Zbl 1475.62007

SpringerBriefs in Applied Statistics and Econometrics. Cham: Springer (ISBN 978-3-030-80064-2/pbk; 978-3-030-80065-9/ebook). xiv, 115 p. (2021).
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Shrinkage estimation for mean and covariance matrices. (English) Zbl 1456.62008

SpringerBriefs in Statistics. JSS Research Series in Statistics. Singapore: Springer (ISBN 978-981-15-1595-8/pbk; 978-981-15-1596-5/ebook). ix, 112 p. (2020).
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Covariance matrix regularization for banded Toeplitz structure via Frobenius-norm discrepancy. (English) Zbl 1433.62139

Ahmed, S. Ejaz (ed.) et al., Matrices, statistics and big data. Selected contributions from IWMS 2016, the 25th international workshop on matrices and statistics, Funchal, Madeira, Portugal, June 6–9, 2016. Cham: Springer. Contrib. Stat., 111-125 (2019).
MSC:  62H12 15B05 62J10
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Asymptotic efficiency in high-dimensional covariance estimation. (English) Zbl 1451.62057

Sirakov, Boyan (ed.) et al., Proceedings of the international congress of mathematicians 2018, ICM 2018, Rio de Janeiro, Brazil, August 1–9, 2018. Volume IV. Invited lectures. Hackensack, NJ: World Scientific; Rio de Janeiro: Sociedade Brasileira de Matemática (SBM). 2903-2923 (2018).
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Covariances in computer vision and machine learning. (English) Zbl 1380.68005

Synthesis Lectures on Computer Vision 13. San Rafael, CA: Morgan & Claypool Publishers (ISBN 978-1-68173-013-4/pbk; 978-1-68173-014-1/ebook). xiii, 156 p. (2018).
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Testing independence via spectral moments. (English) Zbl 1405.62063

Bebiano, Natália (ed.), Applied and computational matrix analysis. MAT-TRIAD, Coimbra, Portugal, September 7–11, 2015. Selected, revised contributions. Cham: Springer (ISBN 978-3-319-49982-6/hbk; 978-3-319-49984-0/ebook). Springer Proceedings in Mathematics & Statistics 192, 263-274 (2017).
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