STATS 605 - Advanced Topics in Modeling and Data Analysis
Section: 001
Term: FA 2017
Subject: Statistics (STATS)
Department: LSA Statistics
Credits:
3
Waitlist Capacity:
99
Advisory Prerequisites:
STATS 601.
Repeatability:
May be repeated for a maximum of 6 credit(s).
Primary Instructor:

This course covers recent developments in statistical modeling and data analysis. Topics include: 1) classification and machine learning, including support vector machines, recursive partitioning, and ensemble methods; 2) methods for analyzing sets of curves, surfaces and images, including functional data analysis, wavelets, independent component analysis, and random field models; 3) modern regression, including splines and generalized additive models; 4) methods for analyzing structured dependent data, including mixed effects models, hierarchical models, graphical models, and Bayesian networks; and 5) clustering detection, and dimension reduction methods, including manifold learning, spectral clustering, and bump hunting.

STATS 605 - Advanced Topics in Modeling and Data Analysis
Schedule Listing
001 (LEC)
P
31780
Closed
0
20STATS PhD only
-
MW 10:00AM - 11:30AM
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