MECfda: Scalar-on-Function Regression with Measurement Error Correction

Solve scalar-on-function linear models, including generalized linear mixed effect model and quantile linear regression model, and bias correction estimation methods due to measurement error. Details about the measurement error bias correction methods, see Luan et al. (2023) <doi:10.48550/arXiv.2305.12624>, Tekwe et al. (2022) <doi:10.1093/biostatistics/kxac017>, Zhang et al. (2023) <doi:10.5705/ss.202021.0246>, Tekwe et al. (2019) <doi:10.1002/sim.8179>.

Package details

AuthorHeyang Ji [aut, cre, ctb, dtc] (<https://orcid.org/0009-0001-7494-7227>), Ufuk Beyaztas [aut, ctb, rev] (<https://orcid.org/0000-0002-5208-4950>), Nicolas Escobar-Velasquez [com] (<https://orcid.org/0009-0006-0800-5692>), Yuanyuan Luan [aut, ctb], Xiwei Chen [aut, ctb], Mengli Zhang [aut, ctb], Roger Zoh [aut, ths], Lan Xue [aut, ths], Carmen Tekwe [aut, ths] (<https://orcid.org/0000-0002-1857-2416>)
MaintainerHeyang Ji <jihx1015@outlook.com>
LicenseGPL-3
Version0.2.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MECfda")

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MECfda documentation built on April 3, 2025, 10:07 p.m.