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1.

図書
図書
1. An introduction to superprocesses
Alison M. Etheridge
出版情報: Providence, R.I. : American Mathematical Society, c2000  xii, 187 p. ; 26 cm
シリーズ名: University lecture series ; v. 20
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2.

図書
図書
2. Green, Brown, and probability & Brownian motion on the line (: pbk ; : hard)
Kai Lai Chung
出版情報: Singapore : World Scientific, c2002  x, 170 p. ; 22 cm
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目次情報: 続きを見る
Preface
Green, Brown, and Probability / Part I.：
Some Notation and Terminology
Green's Ideas / 1.：
Probability and Potential / 2.：
Process / 3.：
Random Time / 4.：
Markov Property / 5.：
Brownian Construct / 6.：
The Trouble with Boundary / 7.：
Return to Green / 8.：
Strong Markov Property / 9.：
Transience / 10.：
Last but not Least / 11.：
Least Energy / 12.：
Addenda
Notes
References
Some Chronology
Appendices
Brownian Motion on the Line / Part II.：
Generalities
Exit and Return
Time and Place
A General Method
Drift
Dirichlet and Poisson Problems
Feynman-Kac Functional
Stopped Feynman-Kac Functional / Part III.：
Introduction
The Results
The Connections
Preface
Green, Brown, and Probability / Part I.：
Some Notation and Terminology
3.

図書
図書
3. Case studies in spatial point process modeling
Adrian Baddeley ... [et al.] (editors)
出版情報: New York : Springer, c2006  xvii, 306 p. ; 24 cm
シリーズ名: Lecture notes in statistics ; 185
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4.

図書
図書
4. Multivariate probability
John H. McColl
出版情報: London : Arnold, c2004  x, 304 p. ; 24 cm
シリーズ名: Arnold texts in statistics
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Fundamentals of probability
Random variables
Transforming and simulating random variables
Bivariate distributions
Random vectors
Sequence of random variables
Functions of a random vector
The multivariate normal distribution
Sampling
useful mathematical results / Appendix A：
tables / Appendix B：
Fundamentals of probability
Random variables
Transforming and simulating random variables
5.

図書
図書
5. An introduction to Markov processes
Daniel W. Stroock
出版情報: Berlin : Springer, c2005  xiv, 171 p. ; 25 cm
シリーズ名: Graduate texts in mathematics ; 230
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Random Walks a Good Place to Begin
Doeblin's Theory for Markov Chains
More about the Ergodic Theory of Markov Chains
Markov Processes in Continuous Time
Reversible Markov Processes
Some Mild Measure Theory
Notation
References
Index
Random Walks a Good Place to Begin
Doeblin's Theory for Markov Chains
More about the Ergodic Theory of Markov Chains
6.

図書
図書
6. Topics in measure theory and real analysis
Alexander B. Kharazishvili
出版情報: Amsterdam ; Paris : Atlantis Press , [Singapore] : World Scientific, c2009  xiv, 461 p. ; 26 cm
シリーズ名: Atlantis studies in mathematics / series editor, J. van Mill ; v. 2
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7.

図書
図書
7. Probability and random processes for electrical and computer engineers (: hardback)
John A. Gubner
出版情報: Cambridge : Cambridge University Press, c2006  xii, 628 p. ; 26 cm
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Preface
Introduction to probability / 1：
Introduction to discrete random variables / 2：
More about discrete random variables / 3：
Continuous random variables / 4：
Cumulative distribution functions and their applications / 5：
Statistics / 6：
Bivariate random variables / 7：
Introduction to random vectors / 8：
Gaussian random vectors / 9：
Introduction to random processes / 10：
Advanced concepts in random processes / 11：
Introduction to Markov chains / 12：
Mean convergence and applications / 13：
Other modes of convergence / 14：
Self similarity and long-range dependence / 15：
Bibliography
Index
Preface
Introduction to probability / 1：
Introduction to discrete random variables / 2：
8.

図書
図書
8. Introduction to stochastic integration (: pbk)
Hui-Hsiung Kuo
出版情報: New York : Springer, c2006  xiii, 278 p. ; 24 cm
シリーズ名: Universitext
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9.

図書
図書
9. Itô calculus. 2nd ed (: pbk)
L.C.G. Rogers and David Williams
出版情報: Cambridge : Cambridge University Press, 2000  xiii, 480 p. ; 23 cm
シリーズ名: Cambridge mathematical library ; . Diffusions, Markov processes, and martingales ; v. 2
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Some frequently used notation
Introduction to Ito calculus / 4：
Some motivating remarks / 4.1：
Some fundamental ideas: previsible processes, localization, etc / 4.2：
The elementary theory of finite-variation processes / 4.3：
Stochastic integrals: the L2 theory / 4.4：
Stochastic integrals with respect to continuous semimartingales / 4.5：
Applications of Ito's formula / 4.6：
Stochastic differential equations and diffusions / 5：
Introduction / 5.1：
Pathwise uniqueness, strong SDEs, flows / 5.2：
Weak solutions, uniqueness in law / 5.3：
Martingale problems, Markov property / 5.4：
Overture to stochastic differential geometry / 5.5：
One-dimensional SDEs / 5.6：
One-dimensional diffusions / 5.7：
The general theory / 6：
Orientation / 6.1：
Debut and section theorems / 6.2：
Optional projections and filtering / 6.3：
Characterising previsible times / 6.4：
Dual previsible projections / 6.5：
The Meyer decomposition theorem / 6.6：
Stochastic integration; the general case / 6.7：
Ito excursion theory / 6.8：
References
Index
Some frequently used notation
Introduction to Ito calculus / 4：
Some motivating remarks / 4.1：
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