Lectures on Stochastic Analysis
by Thomas G. Kurtz
Publisher: University of Wisconsin 2007
Number of pages: 119
The course will introduce stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson random measures, stochastic differential equations for general Markov processes, change of measure, and applications to finance, filtering and control. The intention has been to state the theorems correctly with all hypotheses, but no attempt has been made to include detailed proofs.
Home page url
Download or read it online for free here:
by David A. Kenny - John Wiley & Sons Inc
This text is a general introduction to the topic of structural analysis. It presumes no previous acquaintance with causal analysis. It is general because it covers all the standard, as well as a few nonstandard, statistical procedures.
by T. Devlin, J. Guo, D. Kunin, D. Xiang - Brown University
The intent of the website and these notes is to provide an intuitive supplement to an introductory level probability and statistics course. The level is also aimed at students who are returning to the subject and would like a concise refresher ...
by Klaus Bichteler - University of Texas
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 some functional analysis.
by Muhammad El-Taha - University of Southern Maine
Topics: Data Analysis; Probability; Random Variables and Discrete Distributions; Continuous Probability Distributions; Sampling Distributions; Point and Interval Estimation; Large Sample Estimation; Large-Sample Tests of Hypothesis; etc.