Undergraduate Course: Nonparametric Regression (MATH10052)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) |
Availability | Available to all students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | 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 R.
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Course description |
Not entered
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Information for Visiting Students
Pre-requisites | None |
High Demand Course? |
Yes |
Course Delivery Information
Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Knowledge of methods for nonparametric regression and ability to apply them.
- Ability to study asymptotic properties of nonparametric estimators.
- Ability to use R to fit a nonparametric regression model.
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Contacts
Course organiser | Dr Natalia Bochkina
Tel: 0131 650 8597
Email: n.bochkina@ed.ac.uk |
Course secretary | Mrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email: Alison.Fairgrieve@ed.ac.uk |
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