Probability Models

Erscheinungsjahr 2024
ISBN: 978-0-443-29328-3
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 152 mm x 229 mm

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.

Autoren/Hrsg.

Weitere Mitwirkende

Bai, Zhidong

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

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

Über Autor(innen)

Bai, Zhidong
Dr. Zhidong Bai is currently a full professor at the Northeast Normal University, in China. He obtained his Ph. D. degree in Statistics and Probability from the Department of Mathematics, The University of Science and Technology of China, in 1982. After he obtained his Ph. D. degree, he was subsequently employed as a Lecturer and associate professor at The University of Science and Technology of China, as a research associate at the Center for Multivariate Analysis University of Pittsburgh, as a senior research associate at the Center for Multivariate Analysis, the Penn State University, as an Associate Professor at the Department of Statistics, the Temple University, as a full professor at the Department of Applied Mathematics, the National Sun Yat-sen University, Taiwan, China, as a full professor at the Department of Statistics and Applied Probability, the National University of Singapore, Finally, he moved to the School of Mathematics and Statistics, the Northeast Normal University, China as a full Professor, in October, 2002. During his career, he concentrated on limiting theorems in statistics and probability. His research interests include General Information Criterion, Signal Processing, Image Processing, Robust Estimation, Density, and nonparametric regression estimation, Polya Urn model and applications to adaptive clinical Designs and random matrix theory, After Year 2000, he concentrated his research interest the Spectral Analysis of Large Dimensional Random Matrix and its applications to High Dimensional Statistics. He published nearly 300 research papers and 6 monographs. His research contribution is highly recognized internationally, He was elected as a Fellow of the Third World Academy of Science in 1989 and a Fellow of the Institute of Mathematical Statistics in 1995.