Computational Statistics - STATS521 (2019)
This paper covers maximum likelihood estimation, and the fitting of advanced regression models including non-linear models, mixture models and their generalisations. It will take a practical approach stressing the use of R packages and WinBugs or OpenBugs Bayesian software.
|Prerequisite(s):||STAT321 or STATS321, or three other 300 level Statistics papers, and at the discretion of the Chairperson of Department|
|Internal assessment / examination:||100:0|
Semesters and Locations
|Occurrence Code||When taught||Where taught|
|19A (HAM)||A Semester : 25 Feb 2019 - 23 Jun 2019||Hamilton|
Timetabled Lectures for Computational Statistics (STATS521)
|Tue||4:00 PM||5:00 PM||G.3.33||Feb 25 - Jun 2|
|Thu||3:00 PM||4:00 PM||G.3.33||Feb 25 - Jun 2|
|Fri||4:00 PM||5:00 PM||G.3.33||Feb 25 - Jun 2|
NB:There may be other timetabled events for this paper such as tutorials or workshops.
Visit the online timetable for STATS521 for more details
Indicative Fees for Computational Statistics (STATS521)
Paper Outlines for Computational Statistics (STATS521)
The following paper outlines are available for Computational Statistics (STATS521).
If your paper occurrence is not listed contact the Faculty or School office.
Paper details current as of : 12 November 2019 11:25am
Indicative fees current as of : 12 November 2019 11:10am