Type
PreprintKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionStatistics Program
Date
2018-06-06Permanent link to this record
http://hdl.handle.net/10754/632537
Metadata
Show full item recordAbstract
Varying coefficient models arise naturally as a flexible extension of a simpler model where the effect of the covariate is constant. In this work, we present varying coefficient models in a unified way using the recently proposed framework of penalized complexity (PC) priors to build priors that allow proper shrinkage to the simpler model, avoiding overfitting. We illustrate their application in two spatial examples where varying coefficient models are relevant.Publisher
arXivarXiv
1806.02084Additional Links
http://arxiv.org/abs/1806.02084v1http://arxiv.org/pdf/1806.02084v1