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- W2891418335 abstract "We propose a flexible regression model to study the association between a functional response and multiple functional covariates that are observed on the same domain. Specifically, we relate the mean of the current response to current values of the covariates by a sum of smooth unknown bivariate functions, where each of the functions depends on the current value of the covariate and the time point itself. In this framework, we develop estimation methodology that accommodates realistic scenarios where the covariates are sampled with or without error on a sparse and irregular design, and prediction that accounts for unknown model correlation structure. We also discuss the problem of testing the null hypothesis that the covariate has no association with the response. The proposed methods are evaluated numerically through simulations and two real data applications." @default.
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- W2891418335 date "2018-01-01" @default.
- W2891418335 modified "2023-09-27" @default.
- W2891418335 title "Additive nonlinear functional concurrent model" @default.
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- W2891418335 doi "https://doi.org/10.4310/sii.2018.v11.n4.a11" @default.
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