longke: Nonparametric Predictive Model for Sparse and Irregular Longitudinal Data

The proposed method aims at predicting the longitudinal mean response trajectory by a kernel-based estimator. The kernel estimator is constructed by imposing weights based on subject-wise similarity on L2 metric space between predictor trajectories as well as time proximity. Users could also perform variable selections to derive functional predictors with predictive significance by the proposed multiplicative model with multivariate Gaussian kernels.

Version: 0.1.0
Imports: tidyr, bvls, fdapace, mvtnorm, dplyr, purrr
Published: 2023-07-07
Author: Shixuan Wang [aut, cre], Seonjin Kim [aut], Hyunkeun Cho [aut], Won Chang [aut]
Maintainer: Shixuan Wang <wangs43 at miamioh.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: longke results

Documentation:

Reference manual: longke.pdf

Downloads:

Package source: longke_0.1.0.tar.gz
Windows binaries: r-prerel: longke_0.1.0.zip, r-release: longke_0.1.0.zip, r-oldrel: longke_0.1.0.zip
macOS binaries: r-prerel (arm64): longke_0.1.0.tgz, r-release (arm64): longke_0.1.0.tgz, r-oldrel (arm64): longke_0.1.0.tgz, r-prerel (x86_64): longke_0.1.0.tgz, r-release (x86_64): longke_0.1.0.tgz

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