**Advanced Topics in Probability**

by S.R.S. Varadhan

**Publisher**: New York University 2011**Number of pages**: 203

**Description**:

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.

Download or read it online for free here:

**Download link**

(multiple PDF files)

## Similar books

**Probability on Trees and Networks**

by

**Russell Lyons, Yuval Peres**-

**Cambridge University Press**

This book is concerned with certain aspects of discrete probability on infinite graphs that are currently in vigorous development. Of course, finite graphs are analyzed as well, but usually with the aim of understanding infinite graphs and networks.

(

**1050**views)

**Probability Course**

by

**Gian-Carlo Rota**-

**David Ellerman**

In 1999, Gian-Carlo Rota gave his famous course, Probability, at MIT for the last time. The late John N. Guidi taped the lectures and took notes which he then wrote up in a verbatim manner conveying the substance and the atmosphere of the course.

(

**1740**views)

**Recent Progress on the Random Conductance Model**

by

**Marek Biskup**-

**arXiv**

Recent progress on understanding of the Random Conductance Model is reviewed and commented. A particular emphasis is on the results on the scaling limit of the random walk among random conductances for almost every realization of the environment.

(

**4648**views)

**Lectures on Elementary Probability**

by

**William G. Faris**-

**University of Arizona**

From the table of contents: Combinatorics; Probability Axioms; Discrete Random Variables; The Bernoulli Process; Continuous Random Variables; The Poisson Process; The weak law of large numbers; The central limit theorem; Estimation.

(

**4479**views)