Advanced Topics in Probability
by S.R.S. Varadhan
Publisher: New York University 2011
Number of pages: 203
Topics: Brownian Motion; Continuous Parameter Martingales; Diffusion Processes; Weak convergence and Compactness; Stochastic Integrals and Ito's formula; Markov Processes, Kolmogorov's equations; Stochastic Differential Equations; Existence and Uniqueness; Girsanov Formula; Random Time Change; The two dimensional case; The General Case; Limit Theorems; Reflected Brownian Motion; Reflection in higher dimensions; Invariant Measures.
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by Michael Roeckner - Universitaet Bielefeld
From the table of contents: Introduction to Pathwise Ito-Calculus; (Semi-)Martingales and Stochastic Integration; Markov Processes and Semigroups - Application to Brownian Motion; Girsanov Transformation; Time Transformation.
by Mark Pinsky, Bjorn Birnir - Cambridge University Press
The three main themes of this book are probability theory, differential geometry, and the theory of integrable systems. The papers included here demonstrate a wide variety of techniques that have been developed to solve various mathematical problems.
by Gane Samb Lo - arXiv.org
The fundamental aspects of Probability Theory are presented from a pure mathematical view based on Measure Theory. Such an approach places Probability Theory in its natural frame of Functional Analysis and offers a basis towards Statistics Theory.
by Leif Mejlbro - BookBoon
From the table of contents: Some theoretical background; The binomial distribution; The Poisson distribution; The geometric distribution; The Pascal distribution; The negative binomial distribution; The hypergeometric distribution.