ST5207  Nonparametric Regression

                                                  Semester I, 2009/2010

Instructor:	Dr. Zhang Jin-Ting
Lecture  Time, Venue Final Exam Time, Venue	Tuesday 7-10 pm, LT26 ( Original S16-06-118) Thursday 7-9pm, Dec 3, 2009, LT31
Office/Phone/Fax:	S16/ 07-116,  (65)6516-6749/ 6872-3919
Home Page:	http://www.stat.nus.edu.sg/~zhangjt
E-mail:	stazjt@nus.edu.sg

Prerequisite: Departmental approval

Precluded Modules:  

Modular Credit: 4

Aims & Objectives:   The module aims to introduce various nonparametric techniques that are widely used in data analysis when parametric models are not proper or not available. We mainly focus on techniques for nonparametric density estimation and nonparametric regression. This module is targeted at students who are interested in newly developed statistical techniques for dealing with problems which can not be dealt with using classical parametric statistical methods and are able to meet the pre-requisites.

Main Topics: 

	Nonparametric density estimation: histogram method, kernel density estimation, various bandwidth selection methods, and some asymptotical properties.
	Nonparametric regression modeling: Nadaraya-Watson estimator, local polynomial estimator, various bandwidth selection methods, and some asymptotical properties.

Tutorials: 

One tutorial  per week

Tutorial problems will be posted almost weekly during lectures

Lecture Notes & Tutorial Problems

Tutorial Slot:

Tutorial

Tuesday 9:00-10:00pm

Mode of Assessment: 

Assignments and Tests Policy: 

	Students expected to attend lectures and tutorial sessions regularly
	One  midterm will be scheduled
	Midterm  and final exam  are both closed-book and closed-notes but calculators and a help sheet or two are allowed
	No make-up exams are allowed unless you have Medical Certificates from doctors

Evaluation: 

	Final exam (2 hours)                 60 %
	Midterm test (1  hour and 30 minutes)    30%
	Class/Tutorial Performance   10%

Recommended texts/references

	Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.
	Fan, J. and Gijbels, I (1996). Local polynomial Modelling and its Applications. Chapman and Hall, London.
	Wu, H. and Zhang, J. T. (2006). Nonparametric Regression Methods for Longitudinal Data Analysis: mixed-effects modeling approaches. Wiley, New York.

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