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『簡體書』随机过程用的极限定理 第2版

書城自編碼: 2127138
分類: 簡體書→大陸圖書→自然科學數學
作者: [法]杰克德
國際書號(ISBN): 9787510061387
出版社: 世界图书出版公司
出版日期: 2013-10-01
版次: 1 印次: 1
頁數/字數: 660/
書度/開本: 24开 釘裝: 平装

售價:NT$ 828

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內容簡介:
《随机过程用的极限定理(第2版)(英文)》讲述Apart from correcting a number of printing mistakes,and some mathematical inaccuracies as well,this second edition contains some new material: indeed,during the fifteen years elapsed since the first edition came out,a large number of new results concerning limit theorems have of course been proved by many authors,and more generally mathematical life has been going on.This gave us the feeling that some of the material in the first edition was perhaps not as important as we thought at the time,while there were some neglected topics which have in fact proved to be very useful in various applications.So perhaps a totally new book would have been a good thing to write.Our natural laziness prevented us to do that,but we have felt compelled to fill in the most evident holes in this book.This has been done in the most painless way for us,and also for the reader acquainted with the first edition (at least we hope so ...).That is all new material has been added at the end of preexisting chapters.
目錄
Chapter I. The General Theory of Stochastic Processes,
Semimartingales and Stochastic Integrals
1. Stochastic Basis, Stopping Times, Optional
a-Field,Martingales
 1a. Stochastic Basis
 lb. Stopping Times
 lc. The Optional a-Field
 ld. The Localization Procedure
 1e. Martingales
 1f. The Discrete Case
2. Predictable a-Field, Predictable Times
 2a. The Predictable a-Field
 2b. Predictable Times
 2c. Totally Inaccessible Stopping Times
 2d. Predictable Projection
 2e. The Discrete Case
3. Increasing Processes 
 3a. Basic Properties
 3b. Do, b-Meyer Decomposition and Compensatorsof Increasing
Processes
 3c. Lenglart Domination Property
 3d. The Discrete Case
4. Semimartingales and Stochastic Integrals
 4a. Locally Square-Integrable Martingales
 4b. Decompositions of a Local Martingale
 4c. Semimartingales
 4d. Construction of the Stochastic Integral
 4e. Quadratic Variation ofa Semimartingale and Ito''s Formula
 4f. Dol6ans-Dade Exponential Formula
 4g. The Discrete Case
Chapter II. Characteristics of Semimartingales and Processes with
Independent Increments
1. Random Measures
 1a. General Random Measures
 lb. Integer-Valued Random Measures
 1c. A Fundamental Example: Poisson Measures
 1d. Stochastic Integral with Respect to a Random Measure
2. Characteristics of Semimartingales
 2a. Definition of the Characteristics
 2b. Integrability and Characteristics
 2c. A Canonical Representation for Semimartingales
 2d. Characteristics and Exponential Formula
3. Some Examples
 3a. The Discrete Case
 3b. More on the Discrete Case
 3c. The "One-Point" Point Process and Empirical Processes
4. Semimartingales with Independent Increments
 4a. Wiener Processes
 4b. Poisson Processes and Poisson Random Measures
 4c. Processes with Independent Increments and
Semimartingales
 4d. Gaussian Martingales
5. Processes with Independent Increments
 Which Are Not Semimartingales
 5a. The Results
 5b. The Proofs
6. Processes with Conditionally Independent Increments
7. Progressive Conditional Continuous PIIs
8. Semimartingales, Stochastic Exponential and Stochastic
Logarithm.
 8a. More About Stochastic Exponential and Stochastic
Logarithm.
 8b. Multiplicative Decompositions and
Exponentially Special Semimartingales
Chapter III. Martingale Problems and Changes of Measures
1. Martingale Problems and Point Processes
 1a. General Martingale Problems
 1b. Martingale Problems and Random Measures
 1c. Point Processes and Multivariate Point Processes
……

 

 

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