In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

The classical method of least-squares estimation of the coefficients α in the (matrix) equation y = Zα + e yields estimators α̂ = Ay = + Ae. This method, however, employs only one of a class of ...

Clemens Biller, Adaptive Bayesian Regression Splines in Semiparametric Generalized Linear Models, Journal of Computational and Graphical Statistics, Vol. 9, No. 1 (Mar., 2000), pp. 122-140 ...

GENMOD uses maximum likelihood estimation to fit generalized linear models. This family includes models for categorical data such as logistic, probit, and complementary log-log regression for binomial ...

This course develops ideas first presented in MA100. It consists of the linear algebra part of MA212, covering the following topics: Vector spaces and dimension. Linear transformations, kernel and ...

Since 1987, MCEER, formerly the Multidisciplinary Center for Earthquake Engineering Research (MCEER) and the National Center for Earthquake Engineering Research ( NCEER), has produced over 600 ...