Modern Computational Statistical Methods - STAT878
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 S1 External - Session 1, External (with on campus sessions) |
| Staff Contact(s): | Statistics Staff |
| Prerequisites: |
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| Corequisites: |
((Admission to MAppStat or GradCertAppStat or GradDipAppStat or MActPrac or MDataSc or MSc) and (STAT806 or STAT810)) or (admission to MInfoTech) |
| NCCW(s): | |
| Unit Designation(s): | |
| 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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