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Frontiers of Statistics and Data Science

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.06.2025

Abbildungen

XVIII, 213 p. 27 illus., 16 illus. in color.

Herausgeber

Subhashis Ghosal + weitere

Verlag

Springer Singapore

Seitenzahl

213

Maße (L/B/H)

24,1/16/1,9 cm

Gewicht

466 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9607-41-9

Beschreibung

Portrait


Subhashis Ghoshal
is the Goodnight Distinguished Professor of Statistics at North Carolina State University. He is a Fellow of IMS, ASA and ISBA, and winner of DeGroot Prize for the best book in Statistical Science, 2019, for his book “Fundamentals of Nonparametric Bayesian Inference”. He has written over 150 research articles and advised over 30 doctoral students. He has a variety of research interests including Bayesian inference, nonparametrics, high-dimensional statistics, differential equation models, image processing, and others. His research has been funded NSF, ARO, NSA, Samsung and others, including the prestigious NSF Career Award.


Anindya Roy
 is a Professor of Statistics at the University of Maryland, Baltimore County.  He also holds an appointment with the  US Census Bureau. He is a Fellow of ASA, and  author of a popular textbook “Linear Algebra and Matrix Analysis for Statistics”. His research interests include time series analysis, Bayesian statistics, high-dimensional statistics, data confidentiality, and others.  He has written over 80 research articles and advised over 25 doctoral students. His research has been funded by NSF, NIH, and other funding agencies.

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.06.2025

Abbildungen

XVIII, 213 p. 27 illus., 16 illus. in color.

Herausgeber

Verlag

Springer Singapore

Seitenzahl

213

Maße (L/B/H)

24,1/16/1,9 cm

Gewicht

466 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9607-41-9

Herstelleradresse

Springer-Verlag GmbH
Europaplatz 3
69115 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Frontiers of Statistics and Data Science

  • Chapter 1: Artificial Intelligence in Precision Medicine and Digital Health.- Chapter 2: Revisiting Doob’s Theorem on Posterior Consistency.- Chapter 3: The Central Limit Theorem in High-dimension.- Chapter 4: An Introduction to Deep Learning.- Chapter 5: The R Language and its Use in Statistics.- Chapter 6: Large Deviation Asymptotics for Systems with Fractional Noise.- Chapter 7: High dimensional Wigner matrices with general independent entries.- Chapter 8: Data Analysis after Record Linkage: Sources of Error, Consequences, and Possible Solutions.- Chapter 9: Statistical Inference of Network Data: Past, Present, and Future.- Chapter 10: Current topics in group testing.