GLMlike
GLMlike is a term used in statistics to describe models that are structurally similar to generalized linear models (GLMs) but that relax or modify one or more of GLM’s core components. In a GLM, the response distribution is drawn from the exponential family; the linear predictor η = Xβ enters through a link function g so that g(μ) = η; and a dispersion parameter governs variability. GLMlike models preserve the basic idea of a link between predictors and the mean response but extend beyond the strict GLM framework in various ways.
Common GLMlike extensions include quasi-likelihood or quasi-GLMs that allow overdispersion not captured by the canonical GLM
Estimation and interpretation in GLMlike models often rely on iterative or quasi-likelihood methods, maximum likelihood, or
Applications of GLMlike models are broad, encompassing non-Gaussian data such as counts, binary outcomes, and overdispersed