Modern Computational Statistical Methods - STAT778
This unit offers students the opportunity to study some modern computational methods in statistics. The first half of the unit covers maximum likelihood computations, Bayesian computations using Monte Carlo methods, missing data and the EM algorithm. The second half considers Kernel density estimation, Kernel regression, quantile regression and inferences using Monte-Carlo and bootstrapping methods.
| Credit Points: | 4 |
| When Offered: | S1 Evening - Session 1, North Ryde, Evening |
| Staff Contact(s): | Statistics Staff |
| Prerequisites: |
Admission to MRes |
| Corequisites: | |
| NCCW(s): | STAT878 |
| Unit Designation(s): | |
| Unit Type: | |
| Assessed As: | Graded |
| Offered By: | Department of Mathematics and Statistics Faculty of Science and Engineering |
Course structures, including unit offerings, are subject to change.
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