Pointwise influence matrices for functional-response regression.
Biometrics
; 73(4): 1092-1101, 2017 12.
Article
em En
| MEDLINE
| ID: mdl-28405966
ABSTRACT
We extend the notion of an influence or hat matrix to regression with functional responses and scalar predictors. For responses depending linearly on a set of predictors, our definition is shown to reduce to the conventional influence matrix for linear models. The pointwise degrees of freedom, the trace of the pointwise influence matrix, are shown to have an adaptivity property that motivates a two-step bivariate smoother for modeling nonlinear dependence on a single predictor. This procedure adapts to varying complexity of the nonlinear model at different locations along the function, and thereby achieves better performance than competing tensor product smoothers in an analysis of the development of white matter microstructure in the brain.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
/
Modelos Estatísticos
/
Substância Branca
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Biometrics
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Estados Unidos