GLMmalleissa
GLMmalleissa is a statistical modeling framework described in theoretical literature as an extension of generalized linear models designed to accommodate complex data by incorporating malleable components. The name combines the GLM (generalized linear model) foundation with a set of modular, adjustable components intended to tailor model structure to data characteristics.
GLMmalleissa is proposed as Generalized Linear Models with Malleable Components. The framework adds modular units that
Estimation and fitting rely on the penalized likelihood framework. A typical workflow starts with a base GLM,
Applications include healthcare analytics, econometrics, environmental modeling, and social science research, where data exhibit nonlinear relationships
History and reception: first articulated in theoretical notes and a preprint in 2023; as of 2024 it
See also: GLM, generalized additive models, regularization, link functions.