A computationally efficient three-step marginal method for longitudinal function-on-function regression that fits pointwise scalar-on-function models, smooths along the bivariate domain, and derives confidence bands to enable valid inference on large functional datasets.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Tutorial reviewing and comparing methods to correct measurement error in outcomes and multiple covariates, with a running example, data, and code for reproduction.
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Efficient Longitudinal Function-on-Function Regression
A computationally efficient three-step marginal method for longitudinal function-on-function regression that fits pointwise scalar-on-function models, smooths along the bivariate domain, and derives confidence bands to enable valid inference on large functional datasets.
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Methods to address measurement error in both Outcome and Covariates
Tutorial reviewing and comparing methods to correct measurement error in outcomes and multiple covariates, with a running example, data, and code for reproduction.
- BAMIFun: Bayesian Multiple Imputation for Functional Data