Course Title:

Generalized Linear Models

Textbook:

Generalized Linear Models: with Applications in Engineering and the Sciences, 2nd Edition, Raymond H. Myers, Douglas C. Montgomery, G. Geoffrey Vining, Timothy J. Robinson, John Wiley & Sons, Inc.,

ISBN-13: _978-0-470-45463-3

Prerequisites:

Math 662 and Math 665 or departmental approval

Website:

http://web.njit.edu/~dhar/courses.html

Course Outline

Week

Lecture

Sections

Topic

Assignment

1

1 (9/3)

Chapter 1 and  2.1, 2.2.1

Linear regression (matrix formulation, ordinary least squares (OLS) estimator, Gauss Markov theorem.)

Read Chapter 1. Assignment due 9/10

2

2 (9/10)

2.2.2-2.2.5

Linear regression models (other properties of the OLS estimator, estimation and hypothesis testing)

Assignment due 9/17

3

3 (9/17)

2.2.6-2.5

Linear regression models (residual diagnostics, maximum likelihood estimation [MLE], generalized least squares)

Using R and SAS to perform Regression Analysis. Assignment due 9/24

4

4 (9/24)

2.6-2.7

Linear and nonlinear regression models (weighted least squares, estimation in nonlinear regression models)

Assignment due 10/1

5

5 (10/1)

3.1-3.7

Nonlinear regression models (Gauss-Newton method, inference, weighted nonlinear regression)

Assignment due 10/8

6

6 (10/8)

4.1-4.2.6

Logistic regression models (model description, MLE and dispersion properties, likelihood ratio inference)

Assignment due 10/15

7

7 (10/15)

4.2.7-4.4

Logistic and Poisson regression models (odds ratios, estimation and inference for Poisson regression)

Assignment due 10/29

8

8 (10/22)

MID TERM EXAM October 22, 2013

9

9 (10/29)

5.1-5.2

GLM (components of a GLM, exponential family of distributions, formal structure for the class of GLMs)

Assignment due 11/5

10

10(11/5)

5.3-5.4

GLM (likelihood equations for GLMs, an algorithm for fitting GLMs, quasi-likelihood)

Assignment due 11/12

11

11(11/12)

5.5

GLM (the gamma family, canonical and log links for the gamma family)

Assignment due 11/19

12

12(11/19)

5.6-5.7

GLM (a class of link functions -- the power function, inference for GLMs)

Assignment due 12/3

13

13(12/3)

5.8-5.12, 6.1

GLM and generalized estimating equations (residual analysis for GLMs, layout for longitudinal studies)

Assignment due 12/10

14

14 (12/10)

6.2-6.3

Generalized estimating equations (correlation matrix, identity link, examples)

Ph.D. students cover chapters 7 & 8 as extra reading.

15

12/13 -12/19

Final Exam

IMPORTANT DATES

Night Sections

FIRST DAY OF SEMESTER

Tuesday, September 3, 2013

MIDTERM EXAM

Tuesday, October 22, 2013

LAST DAY TO WITHDRAW

November 4, 2013

LAST DAY OF CLASSES

December 11, 2013

FINAL EXAM PERIOD

December 13-19 (Final exam on Tuesday, December 17, 2013, 6 pm) 

Assignment Weighting

Hand-in Hw and Quizzes

30 %

Midterm Exam I

30 %

Final Exam

40 %

Total                                  100 %