Stochastic Integration and Stochastic Differential Equations
by Klaus Bichteler
Publisher: University of Texas 2002
Number of pages: 643
Written for graduate students of mathematics, physics, electrical engineering, and finance. The students are expected to know the basics of point set topology up to Tychonoff's theorem, general integration theory, and enough functional analysis to recognize the Hahn-Banach theorem.
Home page url
Download or read it online for free here:
by Cosma Rohilla Shalizi
Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Markov Processes, Continuous-Time Processes).
by Thomas G. Kurtz - University of Wisconsin
Covered topics: stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson measures, stochastic differential equations for general Markov processes.
by Cappella Archive - Prasenjit Saha
This is a short book about the principles of data analysis. The emphasis is on why things are done rather than on exactly how to do them. If you already know something about the subject, then working through this book will deepen your understanding.
by Brenda Meery - CK-12.org
CK-12 Foundation's Basic Probability and Statistics– A Short Course is an introduction to theoretical probability and data organization. Students learn about events, conditions, random variables, and graphs and tables that allow them to manage data.