STAT471-12S2 (C) Semester Two 2012

Special Topic in Statistics

0.1250 EFTS
09 Jul 2012 - 11 Nov 2012


Special Topic in Statistics

Special Topic in 2012 - Nonparametric Bayesian Inference

The goal of nonparametric inference is flexibility in modelling and robustness of the resulting inference. In Bayesian nonparametrics, this is achieved through the use of random processes as priors on infinite-dimensional function spaces.

This course looks at some of these priors together with the computational methods for using them. Their use will be illustrated through appications such as density estimation, regression, classification and clustering.

Students should have a sound mathematical background and a good foundation in Statistics and Probability, at least up to the level of STAT213 or STAT214. They should preferably also have taken, or are concurrently taking, STAT314 or STAT461 or a similar course in parametric Bayesian statistics.

For a full list of 2012 Honours courses, please refer to the Department of Mathematics and Statistics Honours Booklet Mathematics and Statistics Honours Booklet

Learning Outcomes

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attributes specified below:

Critically competent in a core academic discipline of their award

Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.

Streams Day Time Where Notes
Stream 01 Wednesday 10:00am-11:00am Erskine 240 9 Jul - 19 Aug,
3 Sep - 14 Oct

Streams Day Time Where Notes
Stream 01 Wednesday 9:00am-10:00am Erskine 033 Lab 1 (Computer Lab) 9 Jul - 19 Aug,
3 Sep - 14 Oct

Course Coordinator

Dominic Lee

Indicative Fees

Domestic fee $788.00

* Fees include New Zealand GST and do not include any programme level discount or additional course related expenses.

For further information see Mathematics and Statistics.

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