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High-Dimensional Covariance Matrix Estimation: An Introduction to Random Matrix Theory - SpringerBriefs in Applied Statistics and Econometrics Aygul Zagidullina 1st ed. 2021 edition
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High-Dimensional Covariance Matrix Estimation: An Introduction to Random Matrix Theory - SpringerBriefs in Applied Statistics and Econometrics
Aygul Zagidullina
It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional setting, and introduces the basic concepts and major results related to spectral statistics and random matrix theory under high-dimensional asymptotics in an understandable and reader-friendly way.
115 pages, 26 Illustrations, color; XIV, 115 p. 26 illus. in color.
| Mediji | Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru) |
| Izlaists | 2021. gada 30. oktobris |
| ISBN13 | 9783030800642 |
| Izdevēji | Springer Nature Switzerland AG |
| Lapas | 115 |
| Izmēri | 155 × 233 × 10 mm · 210 g |
| Valoda | Angļu |
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