Inference in Generalized Additive Mixed Models

@inproceedings{Liny1999InferenceIG,
  title={Inference in Generalized Additive Mixed Models},
  author={UsingSmoothing SplinesbyXihong Liny and Daowen ZhangDepartment},
  year={1999}
}
  • UsingSmoothing SplinesbyXihong Liny, Daowen ZhangDepartment
  • Published 1999
SUMMARY Generalized additive mixed models are proposed for overdispersed and correlated data, which arise frequently in studies involving clustered, hierarchical and spatial designs. This class of models allows for exible functional dependence of an outcome variable on covariates using nonparametric regression, while accounting for correlation among observations using random eeects. We estimate nonparametric functions using smoothing splines, and jointly estimate smoothing parameters and… CONTINUE READING

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