# Holistic Generalized Linear Models

@article{Schwendinger2022HolisticGL, title={Holistic Generalized Linear Models}, author={Benjamin Schwendinger and Florian Schwendinger and Laura Vana}, journal={ArXiv}, year={2022}, volume={abs/2205.15447} }

Holistic linear regression extends the classical best subset selection problem by adding additional constraints designed to improve the model quality. These constraints include sparsity-inducing constraints, sign-coherence constraints and linear constraints. The R package holiglm provides functionality to model and fit holistic generalized linear models. By making use of state-of-the-art conic mixed-integer solvers, the package can reliably solve GLMs for Gaussian, binomial and Poisson…

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