论文标题
整体广义线性模型
Holistic Generalized Linear Models
论文作者
论文摘要
整体线性回归通过添加旨在提高模型质量的其他约束来扩展经典最佳子集选择问题。这些约束包括引起稀疏性的限制，标志连接约束和线性约束。 $ \ textsf {r} $ package $ \ texttt {holiglm} $提供了模型和拟合整体通用线性模型的功能。通过使用最先进的圆锥混合材料求解器，包装可以通过多种整体约束来可靠地解决高斯，二项式和泊松响应的GLM。高级接口简化了约束规范，可以用作$ \ texttt {stats :: glm（）} $ function的置换替换。
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 $\textsf{R}$ package $\texttt{holiglm}$ 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 responses with a multitude of holistic constraints. The high-level interface simplifies the constraint specification and can be used as a drop-in replacement for the $\texttt{stats::glm()}$ function.
