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BIO 329: Matrix Methods for Dynamic Models and Data Analysis

Types of matrices in dynamic & stochastic models, covariances, rectangular data, networks. Spectral theorem, asymptotics, stability theory, Nonnegative matrices, ergodicity, Markov chains. Hermitian, covariance, SVD. Perturbation theory. Random matrix products, Lyapunov exponents. Open to Ph.D. students in Biology. Prerequisites: Calculus (AP level) required. Some knowledge of linear algebra, R, preferred.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit
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