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DRPS : Course Catalogue : School of Mathematics : Mathematics

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.
Entry Requirements
Pre-requisites Students MUST have passed: Foundations of Calculus (MATH08005) AND Several Variable Calculus (MATH08006) AND Linear Algebra (MATH08007) AND Methods of Applied Mathematics (MATH08035) AND Probability (Year 2) (MATH08008) AND Statistics (Year 2) (MATH08051)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Probability (Year 3) (MATH09004) AND Statistics (Year 3) (MATH08052)
Other requirements None
Additional Costs None
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 Splus to fit a nonparametric regression model.
Assessment Information
Degree Examination: 100%.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
Keywords NPR
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 2011 The University of Edinburgh - 31 January 2011 7:59 am