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funbootband: Simultaneous Prediction and Confidence Bands for Functional Data
Computes simultaneous prediction and confidence bands for densely
sampled functional data on a common grid. The calibration builds on the
functional bootstrap approach of Lenhoff et al. (1999)
<doi:10.1016/S0966-6362(98)00043-5>; hierarchical measurement designs are
motivated by Koska et al. (2023)
<doi:10.1016/j.jbiomech.2023.111506>. Independent curves are resampled
individually. Clustered data use an intact-subject bootstrap with equal
subject weighting, and the clustered prediction target is one future
curve from a new subject. Curves are represented by finite Fourier series,
and an 'Rcpp' backend performs the bootstrap calibration.
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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