Semimartingale Theory and Stochastic Calculus
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A01=He/Wang/yan
A01=HeWangyan
A01=Jia-an Yan
A01=Jia-Gang Wang
A01=Sheng-Wu He
absolute continuity in stochastic processes
Author_He/Wang/yan
Author_HeWangyan
Author_Jia-an Yan
Author_Jia-Gang Wang
Author_Sheng-Wu He
Bounded Martingale
Canonical Decomposition
Category=PBWL
Common Jump
Compact Metrizable Space
Conditional Expectation
Continuous Local Martingale
Continuous Martingale Part
Disjoint Graphs
Dual Predictable Projection
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Essential Infimum
Finite Partition
Finite Variation
Integrable Variation
Interval Type
Local Martingale
martingale convergence
mathematics
measure theory applications
Monotone Class
Monotone Class Theorem
Paved Set
point process modeling
Predictable Process
predictable representation
Predictable Set
Predictable Time
probability research
Section Theorems
Semimartingale Theory
Special Semimartingale
stochastic calculus
stochastic process analysis
stochastic processes
Uniformly Integrable
weak convergence probability
Product details
- ISBN 9780849377150
- Weight: 952g
- Dimensions: 156 x 234mm
- Publication Date: 14 Sep 1992
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Semimartingale Theory and Stochastic Calculus presents a systematic and detailed account of the general theory of stochastic processes, the semimartingale theory, and related stochastic calculus. The book emphasizes stochastic integration for semimartingales, characteristics of semimartingales, predictable representation properties and weak convergence of semimartingales. It also includes a concise treatment of absolute continuity and singularity, contiguity, and entire separation of measures by semimartingale approach. Two basic types of processes frequently encountered in applied probability and statistics are highlighted: processes with independent increments and marked point processes encountered frequently in applied probability and statistics.
Semimartingale Theory and Stochastic Calculus is a self-contained and comprehensive book that will be valuable for research mathematicians, statisticians, engineers, and students.
He Sheng-Wu, Jia-Gang Wang, Jia-an Yan
