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. The computing software MATLAB, R and WinBUGS are used.
| Credit Points: | 4 |
| When Offered: | S1 Evening - Session 1, North Ryde, Evening S1 External - Session 1, External (On-campus sessions: None) |
| Staff Contact(s): | Associate Professor Jun Ma |
| 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 Statistics Faculty of Science and Engineering |
Course structures, including unit offerings, are subject to change.
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