Current MSCS Graduate Courses ( Fall 2009, Spring 2010 )
Fall 2009
STAT 501
Probability Theory I
(J. Yang)
- PREREQUISITES:
- MATH 534 or consent of instructor.
- DESCRIPTION:
- Abstract measure theory, probability measures, Kolmogorov extension theorem, sums of independent random variables, the strong and weak laws of large numbers, the central limit theorem, characteristic functions, law of iterated logarithm, infinitely divisible laws.
STAT 591
Advanced Topics in Statistics, Probability, and Operation Research
(T.E.S. Raghavan)
- PREREQUISITES:
- Students who have taken Stat 473, Stat 471, or Stat 461 are ideally suited for this course. Note that without some introductory exposure to at least one of these courses, students may not find it easy. Students from Engineering departments may find the course close to their research interests.
- DESCRIPTION:
- Course Title: Algorithms and Existence Theorems for Stochastic Games. Topics are parts of the fast growing area of Algorithmic Game Theory. Closely related topics include Markov decisions and Learning Theory. Key topics include dynamic games whose equilibrium strategies are tractable in finite arithmetic steps via standard algorithms like the simplex algorithm or Lemke Howson's complementary pivoting algorithm. Text book: Competitive Markov Decision Process by J.A. Filar and O.J. Vrieze, Springer Verlag Graduate Text Book Series. (1996).
Spring 2010
STAT 502
Probability Theory II
(J. Yang)
- PREREQUISITES:
- Stat 501.
- DESCRIPTION:
- Radon-Nikodym theorem, conditional expectations, martingales, stationary processes, ergodic theorem, stationary Gaussian processes, Markov chains, introduction to stochastic processes, Brownian motions.
STAT 591
Advanced Topics in Statistics, Probability, and Operation Research
(Jing Wang)
- PREREQUISITES:
- Stat 411.
- DESCRIPTION:
- Nonparametric and semiparametric density and regression estimation, kernel smoothing, polynomial spline, penalized spline, tuning parameter selection criterion, parametric model testing and diagnosis, generalized additive model, and nonlinear time series.