Regression modelDistributional regression
广义可加模型位置、尺度和形状（GAMLSS）
将普通回归设想为仅根据预测变量的变化来调整钟形曲线的中心。GAMLSS更进一步：它允许整个响应分布的宽度、不对称性和尾部厚度随预测变量变化。如果较高的学生不仅平均得分更高，而且得分变异性更大，并且这种变异性本身遵循某种模式，那么GAMLSS可以通过为每个分布参数拟合一个单独的平滑函数来一次性捕捉所有这些特征。
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来源
- Rigby, R. A., & Stasinopoulos, D. M. (2005). Generalized additive models for location, scale and shape. Journal of the Royal Statistical Society: Series C, 54(3), 507–554. DOI: 10.1111/j.1467-9876.2005.00510.x ↗
如何引用本页
ScholarGate. (2026, June 2). Generalized Additive Models for Location, Scale and Shape (GAMLSS). ScholarGate. https://scholargate.app/zh/statistics/gamlss
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 广义可加模型 (GAM)机器学习↔ compare
- 分位数回归计量经济学↔ compare