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, ...

Bo Wang, Jian Qing Shi, Generalized Gaussian Process Regression Model for Non-Gaussian Functional Data, Journal of the American Statistical Association, Vol. 109, No. 507 (September 2014), pp.

Generalized Linear Models and Categorical Data Analysis in R Course Topics Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an ...

We investigated the risk factors for childhood malnutrition in India based on the 2005/2006 Demographic and Health Survey by applying a novel estimation technique for additive quantile regression.

Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of-fit analyses. Census tracts. Fire ...