Course Schedule - Spring Semester 2016

     

STAT 648 001 (CRN: 22758)

GRAPH MODELS & NETWORKS

Long Title: GRAPHICAL MODELS AND NETWORKS
Department: Statistics
Instructor: Schweinberger, Michael
Meeting: 2:30PM - 3:45PM TR DCH 1042 (11-JAN-2016 - 22-APR-2016) 
Session: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
 
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Prerequisites: STAT 519
Section Max Enrollment: 49
Section Enrolled: 6
Enrollment data as of: 28-JAN-2023 7:52PM
 
Additional Fees: None
 
Final Exam: GR Course-Dept Schedules Exam
 
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.