Martingale Methods in Statistics

Regular price €137.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Yoichi Nishiyama
advanced probability theory
asymptotic inference
Author_Yoichi Nishiyama
Category=PBT
Category=PBTB
Central limit theorems
change point detection in statistics
Change point problem
Change Point Problems
Conditional Expectations
Continuous Local Martingales
Continuous Mapping Theorem
Counting Process Models
Cox's Regression Model
Diffusion Process Models
Discrete Time Martingales
Doob Meyer Decomposition
Doob Meyer Decomposition Theorem
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Estimating equation
high-frequency data modeling
Homogeneous Poisson Process
Inhomogeneous Poisson Process
Local asymptotic normality
Local Martingale
Markov chain statistics
Martingale Central Limit Theorem
Martingale Transformation
Maximal inequality
MLEs
Optional Sampling Theorem
Partial Sum Process
Predictable Compensator
Predictable Quadratic Variation
semimartingale techniques
Standard Wiener Process
Stochastic Basis
Stochastic Integrals
Stochastic Process
survival analysis methods
Vasicek Process
Z-estimator

Product details

  • ISBN 9781466582811
  • Weight: 640g
  • Dimensions: 156 x 234mm
  • Publication Date: 24 Nov 2021
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

Martingale Methods in Statistics provides a unique introduction to statistics of stochastic processes written with the author’s strong desire to present what is not available in other textbooks. While the author chooses to omit the well-known proofs of some of fundamental theorems in martingale theory by making clear citations instead, the author does his best to describe some intuitive interpretations or concrete usages of such theorems. On the other hand, the exposition of relatively new theorems in asymptotic statistics is presented in a completely self-contained way. Some simple, easy-to-understand proofs of martingale central limit theorems are included.

The potential readers include those who hope to build up mathematical bases to deal with high-frequency data in mathematical finance and those who hope to learn the theoretical background for Cox’s regression model in survival analysis. A highlight of the monograph is Chapters 8-10 dealing with Z-estimators and related topics, such as the asymptotic representation of Z-estimators, the theory of asymptotically optimal inference based on the LAN concept and the unified approach to the change point problems via "Z-process method". Some new inequalities for maxima of finitely many martingales are presented in the Appendix. Readers will find many tips for solving concrete problems in modern statistics of stochastic processes as well as in more fundamental models such as i.i.d. and Markov chain models.

Yoichi Nishiyama is a professor in mathematical statistics and probability at the School of International Liberal Studies of Waseda University; he is also engaged in the education of master’s and doctoral students at the Department of Pure and Applied Mathematics at the same university. Prior to his assignment to Waseda University, he worked at the Institute of Statistical Mathematics, Tokyo, from 1994 to 2015. He was the Editor-in-Chief of Journal of the Japan Statistical Society and a Co-Editor of Annals of the Institute of Statistical Mathematics and he received the JSS Ogawa Award from the Japan Statistical Society in 2009.

More from this author