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 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 Gian-Carlo Rota, Kenneth Baclawski
The purpose of the text is to learn to think probabilistically. The book starts by giving a bird's-eye view of probability, it first examines a number of the great unsolved problems of probability theory to get a feeling for the field.
by Remco van der Hofstad - Eindhoven University of Technology
These lecture notes are intended to be used for master courses, where the students have a limited prior knowledge of special topics in probability. We have included many of the preliminaries, such as convergence of random variables, etc.
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.