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fdaconcur
View on CRAN: Click
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Download and install fdaconcur package within the R console
Install from CRAN:
install.packages("fdaconcur")
Install from Github:
library("remotes")
install_github("cran/fdaconcur") Install by package version:
library("remotes")
install_version("fdaconcur", "0.1.3") Attach the package and use:
library("fdaconcur")
Maintained by
Su I Iao
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[Scholar Profile | Author Map]
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First Published: 2022-09-20
Latest Update: 2024-07-20
Description:
Provides an implementation of concurrent or varying coefficient regression methods for
functional data. The implementations are done for both dense and sparsely observed functional
data. Pointwise confidence bands can be constructed for each case. Further, the influence of
past predictor values are modeled by a smooth history index function,
while the effects on the response are described by smooth varying coefficient functions,
which are very useful in analyzing real data such as COVID data.
References: Yao, F., M
How to cite:
Su I Iao (2022). fdaconcur: Concurrent Regression and History Index Models for Functional Data. R package version 0.1.3, https://cran.r-project.org/web/packages/fdaconcur. Accessed 15 Jul. 2026.
Previous versions and publish date:
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Complete documentation for fdaconcur
Functions, R codes and Examples using
the fdaconcur R package
Some associated functions: ConcReg_Lag . ConcurReg . GetCI_Dense . GetCI_Sparse . fitted_ptFCReg . historyIndexDense . historyIndexSparse . ptFCReg . smPtFCRegCoef .
Some associated R codes: CI_dense_FCReg.R . CI_sparse_FCReg.R . CVLwls1D.R . ConcReg_Lag.R . ConcurReg.R . GCVLwls1D1.R . GetEigenAnalysisResults.R . GetSmoothedMeanCurve.R . HandleNumericsAndNAN.R . fitted_ptFCReg.R . historyIndexDense.R . historyIndexSparse.R . ptFCReg.R . smPtFCRegCoef.R . Full fdaconcur package functions and examples
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