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 ...

General Linear Models An analysis-of-variance model can be written as a linear model, which is an equation that predicts the response as a linear function of parameters and design variables. In ...

James T. Thorson, Mayumi L. Arimitsu, Taal Levi, Gretchen H. Roffler, Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie, Ecology, Vol. 103, No. 5 ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...

Yuanzhi Huang, Steven G. Gilmour, Kalliopi Mylona, Peter Goos, Optimal design of experiments for non-linear response surface models, Journal of the Royal Statistical Society. Series C (Applied ...