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Frontiers of Statistics and Data Science

This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily...

詳細記述

保存先:
書誌詳細
団体著者: SpringerLink (Online service)
その他の著者: Ghosal, Subhashis (編集者), Roy, Anindya (編集者)
フォーマット: 電子媒体 eBook
言語:英語
出版事項: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
版:1st ed. 2025.
シリーズ:IISA Series on Statistics and Data Science,
主題:
Machine learning.
Biometry.
Artificial intelligence > Data processing.
Probabilities.
Machine Learning.
Biostatistics.
Data Science.
Applied Probability.
オンライン･アクセス:https://doi.org/10.1007/978-981-96-0742-6
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目次:
  • 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.

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