Undergraduate Course: Nonparametric Regression (MATH10052)
Course Outline
| School |
School of Mathematics |
College |
College of Science and Engineering |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 10 (Year 4 Undergraduate) |
Credits |
10 |
| Home subject area |
Mathematics |
Other subject area |
Specialist Mathematics & Statistics (Honours) |
| Course website |
http://student.maths.ed.ac.uk |
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| Course description |
Course for final year students in Honours programmes in Mathematics.
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 methods such as kernel and spline smoothing, with emphasis on nonparametric wavelet regression. We will see how these methods can be applied in practice using Splus. |
Course Delivery Information
Summary of Intended Learning Outcomes
1. Knowledge of methods for nonparametric regression and ability to apply them.
2. Familiarity with the Bayesian approach in wavelet nonparametric regression.
3. Ability to use Splus to fit a nonparametric regression model.
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Assessment Information
Degree Examination: 100%.
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| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Liam O'Carroll
Tel: (0131 6)50 5070
Email: L.O'Carroll@ed.ac.uk |
Course secretary |
Ms Jennifer Marshall
Tel: (0131 6)50 5048
Email: Jennifer.Marshall@ed.ac.uk |
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copyright 2010 The University of Edinburgh -
1 September 2010 6:18 am
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