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 ...

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 ...

Canonical correlation has been little used and little understood, even by otherwise sophisticated analysts. An alternative approach to canonical correlation, based on a general linear multivariate ...

Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very ...

Hoerl and Kennard introduced a class of biased estimators (ridge estimators) for the parameters in an ill-conditioned linear model. In this paper the ridge estimators are viewed as a subclass of the ...