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Full-Text Articles in Life Sciences
Fast, Flexible Function-On-Scalar Regression, With An Application To Brain Development, Philip T. Reiss, Lei Huang
Fast, Flexible Function-On-Scalar Regression, With An Application To Brain Development, Philip T. Reiss, Lei Huang
Philip T. Reiss
No abstract provided.
Functional Generalized Linear Models With Images As Predictors, Philip T. Reiss, R. Todd Ogden
Functional Generalized Linear Models With Images As Predictors, Philip T. Reiss, R. Todd Ogden
Philip T. Reiss
Functional principal component regression (FPCR) is a promising new method for regressing scalar outcomes on functional predictors. In this paper we present a theoretical justification for the use of principal components in functional regression. FPCR is then extended in two directions: from linear to the generalized linear modeling, and from univariate signal predictors to high-resolution image predictors. We show how to implement the method efficiently by adapting generalized additive model technology to the functional regression context. A technique is proposed for estimating simultaneous confidence bands for the coefficient function; in the neuroimaging setting, this yields a novel means to identify …