Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

Ying Ding, Bin Nan, A SIEVE M-THEOREM FOR BUNDLED PARAMETERS IN SEMIPARAMETRIC MODELS, WITH APPLICATION TO THE EFFICIENT ESTIMATION IN A LINEAR MODEL FOR CENSORED DATA, The Annals of Statistics, Vol.

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

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 ...