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 ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 37, No. 2 (June/juin 2009), pp. 219-234 (16 pages) In many applications of generalized linear mixed models to clustered ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 45, No. 4 (1996), pp. 407-436 (30 pages) The authors review the applications of generalized linear models to actuarial ...

where y i is the response variable for the ith observation. The quantity x i is a column vector of covariates, or explanatory variables, for observation i that is known from the experimental setting ...

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 MPhil/PhD in Statistics, MSc in Data ...

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