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, ...

A hybrid method that combines Laplace's approximation and Monte Carlo simulations to evaluate integrals in the likelihood function is proposed for estimation of the parameters in nonlinear mixed ...

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 ...

We propose a general Bayesian method of comparing models. The approach is based on the Kullback-Leibler distance between two families of models, one nested within the other. For each parameter value ...

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 ...

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Financial Mathematics and Statistics, BSc in Mathematics with ...

In the early 1970s, statisticians had difficulty in analysing data where the random variation of the errors did not come from the bell-shaped normal distribution. Besides normality, these traditional ...