Journal article
Incorporating covariates in skewed functional data models
M Li, AM Staicu, HD Bondell
Biostatistics | OXFORD UNIV PRESS | Published : 2015
Abstract
We introduce a class of covariate-Adjusted skewed functional models (cSFM) designed for functional data exhibiting location-dependent marginal distributions. We propose a semi-parametric copula model for the pointwise marginal distributions, which are allowed to depend on covariates, and the functional dependence, which is assumed covariate invariant. The proposed cSFM framework provides a unifying platform for pointwise quantile estimation and trajectory prediction. We consider a computationally feasible procedure that handles densely as well as sparsely observed functional data. The methods are examined numerically using simulations and is applied to a new tractography study of multiple sc..
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Awarded by National Cancer Institute
Funding Acknowledgements
Staicu's research was supported by NSF grant DMS 1007466 and NIH grant 1R01NS085211-01. Bondell's research was supported by NSF grant DMS-1308400 and NIH grant P01-CA-142538.