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MATH 680 — Computation Intensive Statistics

General introduction to computational methods in statistics; optimization methods; EM algorithm; random number generation and simulations; bootstrap, jackknife, cross-validation, resampling and permutation; Monte Carlo methods: Markov chain Monte Carlo and sequential Monte Carlo; computation in the R language.

  • Credits: 4
  • Faculty: Graduate Studies
  • Department: Mathematics and Statistics
  • Taught by: Archer Yi Yang
  • Prerequisites: MATH 556, MATH 557 or permission of instructor

Sections offered

  • Section 001 (Lec), Tue Thu 11:35 am-12:55 pm — 8 seats open