refund: Regression with Functional Data

Canonical link: https://rscholar.com/pkg/refund

Jeff Goldsmith • Fabian Scheipl • Lei Huang • Julia Wrobel • Chongzhi Di • Jonathan Gellar • Jaroslaw Harezlak • Mathew W. McLean • Bruce Swihart • Luo Xiao • Ciprian Crainiceanu • Philip T. Reiss • Yakuan Chen • Sonja Greven • Lan Huo • Madan Gopal Kundu • So Young Park • David L. Miller • Ana-Maria Staicu • Erjia Cui • Ruonan Li • Zheyuan Li • View description and downloads View dependencies GitHub project

2010 Published

0 Citations

22 Authors

31 Revisions

0.1-37 Version

GPL-2 License

Referenced by ⇅	Year
FDboost: Boosting Functional Regression Models (Version 1.1-2)	2014
MJMbamlss: Multivariate Joint Models with 'bamlss' (Version 0.1.0)	2023
fPASS: Power and Sample Size for Projection Test under Repeated Measures (Version 1.0.0)	2023
fastFMM: Fast Functional Mixed Models using Fast Univariate Inference (Version 0.3.0)	2023
funmediation: Functional Mediation for a Distal Outcome (Version 1.0.2)	2021
ghcm: Functional Conditional Independence Testing with the GHCM (Version 3.0.1)	2021
gmfamm: Generalized Multivariate Functional Additive Models (Version 0.1.0)	2024
longsurr: Longitudinal Surrogate Marker Analysis (Version 1.0)	2022
mMARCH.AC: Processing of Accelerometry Data with 'GGIR' in mMARCH (Version 2.9.4.0)	2022
mlr: Machine Learning in R (Version 2.19.2)	2013
mxfda: A Functional Data Analysis Package for Spatial Single Cell Data (Version 0.2.2)	2024
postGGIR: Data Processing after Running 'GGIR' for Accelerometer Data (Version 2.4.0.2)	2021
refund.shiny: Interactive Plotting for Functional Data Analyses (Version 1.0)	2015
rmfanova: Repeated Measures Functional Analysis of Variance (Version 0.1.0)	2023
runDRT: Run Doubly Ranked Tests (Version 0.1.0)	2024
sparseFLMM: Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data (Version 0.4.1)	2017
spfda: Function-on-Scalar Regression with Group-Bridge Penalty (Version 0.9.1)	2020
tf: S3 Classes and Methods for Tidy Functional Data (Version 0.3.4)	2024

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