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In den WarenkorbZustand: New.
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In den WarenkorbPaperback. Zustand: Brand New. 291 pages. 9.21x6.14x0.71 inches. In Stock.
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In den WarenkorbEinband - flex.(Paperback). Zustand: New. Arup Bose is a Professor at the Indian Statistical Institute, Kolkata, India. He is a distinguished researcher in Mathematical Statistics and has been working in high-dimensional random matrices for the last fifteen years. He has been th.
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In den WarenkorbZustand: New.
Sprache: Englisch
Verlag: Taylor & Francis Ltd Dez 2020, 2020
ISBN 10: 036773446X ISBN 13: 9780367734466
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Large dimensional random matrices (LDRM) with specific patterns arise in econometrics, computer science, mathematics, physics, and statistics. This book provides an easy initiation to LDRM. Through a unified approach, we investigate the existence and properties of the limiting spectral distribution (LSD) of different patterned random matrices as the dimension grows. The main ingredients are the method of moments and normal approximation with rudimentary combinatorics for support. Some elementary results from matrix theory are also used. By stretching the moment arguments, we also have a brush with the intriguing but difficult concepts of joint convergence of sequences of random matrices and its ramifications.
EUR 166,73
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In den WarenkorbGebunden. Zustand: New. Large dimensional random matrices (LDRM) with specific patterns arise in econometrics, computer science, mathematics, physics, and statistics. This book provides an easy initiation to LDRM. Through a unified approach, we investigate the existence and pro.
Sprache: Englisch
Verlag: Taylor & Francis Ltd Mai 2018, 2018
ISBN 10: 1138591467 ISBN 13: 9781138591462
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - 'This book focuses on the limit spectral distribution (LSD) of patterned random matrices and provides a comprehensive variety of LSD results. It is accessible to first or second years Master's students and uses very elementary techniques. It is suitable for a beginner in random matrices with some probability background'.