THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2019/2020

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Nonparametric Regression Models (MATH11186)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryA 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Honours Complex Variables (MATH10067) AND Statistical Methodology (MATH10095) OR ( Linear Statistical Modelling (MATH10005) AND Likelihood (MATH10004))
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Nonparametric Regression (MATH10052)
Other requirements None
Course Delivery Information
Academic year 2019/20, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 5, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 69 )
Assessment (Further Info) Written Exam 95 %, Coursework 5 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 5%; Examination 95%
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)Nonparametric Regression Models (MATH11186)2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand a range of methods for nonparametric regression and be able to apply them.
  2. Study asymptotic properties of nonparametric estimators.
  3. Use R to fit nonparametric regression models.
Reading List
None
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.
KeywordsNRM,Nonparametric,Statistics
Contacts
Course organiserDr Natalia Bochkina
Tel: 0131 650 8597
Email: n.bochkina@ed.ac.uk
Course secretaryMiss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk
Navigation
Help & Information
Home
Introduction
Glossary
Search DPTs and Courses
Regulations
Regulations
Degree Programmes
Introduction
Browse DPTs
Courses
Introduction
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Prospectuses
Important Information