DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Nonparametric Regression Models (MATH11186)

 School School of Mathematics College College of Science and Engineering Credit level (Normal year taken) SCQF Level 11 (Postgraduate) Availability Not available to visiting students SCQF Credits 10 ECTS Credits 5 Summary 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 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.
 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
 Academic year 2017/18, 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
 On completion of this course, the student will be able to: understand a range of methods for nonparametric regression and be able to apply them.study asymptotic properties of nonparametric estimators.use R to fit nonparametric regression models.
 None
 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. Keywords NRM,Nonparametric,Statistics
 Course organiser Dr Jonathan Gair Tel: (0131 6)50 4897 Email: J.Gair@ed.ac.uk Course secretary Mrs Frances Reid Tel: (0131 6)50 4883 Email: f.c.reid@ed.ac.uk
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