Course Schedule - Spring Semester 2014

     

Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).
Additional information available here.

STAT 648 001 (CRN: 22758)

GRAPH MODELS & NETWORKS

Long Title: GRAPHICAL MODELS AND NETWORKS
Department: Statistics
Instructor: Schweinberger, Michael
Meeting: 1:00PM - 2:15PM TR (13-JAN-2014 - 25-APR-2014) 
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
 
Prerequisites: STAT 431
Section Max Enrollment: 50
Section Enrolled: 20
Enrollment data as of: 4-MAY-2024 1:22AM
 
Additional Fees: None
 
Final Exam: Final Exam Unknown
 
Description: Graphical models – aka Bayes networks, Markov networks, Gaussian networks, etc. – have been widely used to represent complex phenomena with dependence. The course aims to stimulate interest in graphical models and covers directed and undirected graphical models, exponential-family representations of graphical models, statistical inference, finite-sample and large-sample properties, and applications.