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. 40, No. 4, Special Issue in Honour of Mary Thompson (December/décembre 2012), pp. 745-769 (25 pages) In this paper, we ...

Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K ...

You construct a generalized linear model by deciding on response and explanatory variables for your data and choosing an appropriate link function and response probability distribution. Some examples ...