STATS 201C
Advanced Modeling and Inference
Statistics · 4 units · Graduate courses (200-299)
Designed for graduate students. Introduction to advanced topics in statistical modeling and inference, including Bayesian hierarchical models, missing data problems, mixture modeling, additive modeling, hidden Markov models, and Bayesian networks. Coverage of computational methods used and developed for these models and problems, such as EM algorithm, data augmentation, dynamic programming, and belief propagation.
S/U or letter grading.
Requisites
Official UCLA wording
Strongly recommended requisites: courses 200B, 201B.
BruinTree reads · Recommended
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
STATS 201C
- STATS 200BTheoretical Statistics
- STATS 201BStatistical Modeling and Learning
- STATS 200AApplied Probability
- STATS 201AResearch Design, Sampling, and Analysis
2 direct requisites. Showing 6 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
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What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.