Postgraduate Course: Nonparametric Regression Models (MATH11186)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | A regression function is an important tool for describing the relation between two or more random variables. In real life problems, this function is usually unknown but can be estimated from a sample of observations. Nonparametric methods are flexible techniques dedicated to treat general cases where the shape of the regression curve is unknown.
In this course we will introduce nonparametric regression models and their application in practice using R. |
Course description |
Topics to be covered includes :
- splines;
- general additive models;
- kernel estimation;
- wavelets; and
- the use of R for fitting nonparametric models.
|
Course Delivery Information
Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand a range of methods for nonparametric regression and be able to apply them.
- Study asymptotic properties of nonparametric estimators.
- Use R to fit nonparametric regression models.
|
Additional Information
Graduate Attributes and Skills |
Not entered |
Special Arrangements |
These Postgraduate Taught courses may be taken by Undergraduate students *without* requiring a concession (NB. students on Postgraduate taught programmes are given priority in the allocation of places). For all other Postgraduate Taught courses the student and/or Personal Tutor must seek a concession. |
Keywords | NRM,Nonparametric,Statistics |
Contacts
Course organiser | Dr Natalia Bochkina
Tel: 0131 650 8597
Email: n.bochkina@ed.ac.uk |
Course secretary | Miss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk |
|
|