This unit builds on the basic ideas of linear models introduced in Statistics 1 (MATH 11400) and Linear Models (MATH 35110), and extends them to deal with more general specifications.

Specialization: Statistical Modeling for Data Science Applications Instructor: Brian Zaharatos, Director, Professional Master’s Degree in Applied Mathematics Prior knowledge needed: Differentiation, ...

Students must have completed: EITHER Probability, Distribution Theory and Inference (ST202) OR Probability and Distribution Theory (ST206) AND Mathematical Methods (MA100) or equivalent. It is assumed ...

Applied Regression Analysis and Generalized Linear Models Frees, E.W. (2010). Regression Modeling with Actuarial and Financial Applications Assessment Exam (70%, duration: 2 hours) in the January exam ...

LEE H. DICKER, Variance estimation in high-dimensional linear models, Biometrika, Vol. 101, No. 2 (JUNE 2014), pp. 269-284 ...

This paper develops an asymptotic theory for estimated change-points in linear and nonlinear time series models. Based on a measurable objective function, it is shown that the estimated change-point ...

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information. Unit name Generalised Linear Models Unit code ...