The generalized least squares estimator (GLSE) and the feasible generalized least squares estimator (FGLSE) are, separately, extended to the generalized and the ...

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, ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 57, No. 1 (2008), pp. 75-87 (13 pages) Complex survey sampling is often used to sample a fraction of a large finite ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

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

This course is compulsory on the MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available on the MPhil/PhD in Statistics, MSc in Data ...

In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

This course is compulsory on the MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available on the MSc in Data Science, MSc in Health Data ...