by S. R. S. Varadhan
Publisher: New York University 2000
Number of pages: 300
These notes are based on a first year graduate course on Probability and Limit theorems given at Courant Institute of Mathematical Sciences. The text covers discrete time processes. A small amount of measure theory is included.
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by David Nualart - The University of Kansas
From the table of contents: Stochastic Processes (Probability Spaces and Random Variables, Definitions and Examples); Jump Processes (The Poisson Process, Superposition of Poisson Processes); Markov Chains; Martingales; Stochastic Calculus.
by H.R. Pitt - Tata institute of Fundamental Research
Measure Theory (Sets and operations on sets, Classical Lebesgue and Stieltjes measures, Lebesgue integral); Probability (Function of a random variable, Conditional probabilities, Central Limit Problem, Random Sequences and Convergence Properties).
by Rick Durrett - Cambridge University Press
An introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It concentrates on the results that are the most useful for applications.
by E. T. Jaynes - Cambridge University Press
The book is addressed to readers familiar with applied mathematics at the advanced undergraduate level. The text is concerned with probability theory and all of its mathematics, but now viewed in a wider context than that of the standard textbooks.