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 |
Taught in Gaelic? | No |
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. |
Information for Visiting Students
Pre-requisites | None |
Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
Not being delivered |
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 R to fit a nonparametric regression model.
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Assessment Information
Degree Examination: 100%.
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Special Arrangements
None |
Additional Information
Academic description |
Not entered |
Syllabus |
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Transferable skills |
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Reading list |
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Study Abroad |
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Study Pattern |
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Keywords | NPR |
Contacts
Course organiser | Dr Natalia Bochkina
Tel: 0131 650 8597
Email: |
Course secretary | Mrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email: |
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