統計学ハンドブック 第５１巻：確率モデル Probability Models (Handbook of Statistics)

Srinivasa Rao, Arni S.R. (EDT)/ Bai, Zhidong (EDT)/ Rao, C.R. (EDT)

Academic Press Inc（2024/09発売）

• 製本 Hardcover:ハードカバー版／ページ数 520 p.
• 言語 ENG
• 商品コード 9780443293283
• DDC分類 519.22

Full Description

Probability Models, Volume 51 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on Stein's methods, Probabilities and thermodynamics third law, Random Matrix Theory, General tools for understanding fluctuations of random variables, An approximation scheme to compute the Fisher-Rao distance between multivariate normal distributions, Probability Models Applied to Reliability and Availability Engineering, Backward stochastic differential equation- Stochastic optimization theory and viscous solution of HJB equation, and much more.

Additional chapters cover Probability Models in Machine Learning, The recursive stochastic algorithm, randomized urn models and response-adaptive randomization in clinical trials, Random matrix theory: local laws and applications, KOO methods and their high-dimensional consistencies in some multivariate models, Fourteen Lectures on Inference for Stochastic Processes, and A multivariate cumulative damage model and some applications.

Contents

Preface
Arni S.R. Srinivasa Rao, Zhidong Bai and C.R. Rao
1. Stein's methods
Qi-Man Shao and Zhuosong Zhang
2. Probabilities and thermodynamics third law
Angelo Plastino
3. Random Matrix Theory
Jeff Yao
4. General tools for understanding fluctuations of random variables
Sourav Chatterjee
5. An approximation scheme to compute the Fisher-Rao distance between multivariate normal distributions
Frank Nielsen
6. Chapter title to be confirmed
Qihua Wang
7. Probability Models Applied to Reliability and Availability Engineering
Kishor Trivedi, Kishor Trivedi and Liudong Xing
8. Backward stochastic differential equation- Stochastic optimization theory and viscous solution of HJB equation
Shige Peng
9. Probability Models in Machine Learning
Qi Meng
10. Chapter title to be confirmed
Grzegorz A. Rempala
11. The recursive stochastic algorithm, randomized urn models and response-adaptive randomization in clinical trials
Lixin Zhang
12. Random matrix theory: local laws and applications
Fan Yang, Yukun He and Zhigang Bao
13. KOO methods and their high-dimensional consistencies in some multivariate models
Y. Fujikoshi
14. Fourteen Lectures on Inference for Stochastic Processes
B.L.S. PRAKASA RAO
15. A multivariate cumulative damage model and some applications
Raul Fierro