Other packages > Find by keyword >

funreg  

Functional Regression for Irregularly Timed Data
View on CRAN: Click here


Download and install funreg package within the R console
Install from CRAN:
install.packages("funreg")

Install from Github:
library("remotes")
install_github("cran/funreg")

Install by package version:
library("remotes")
install_version("funreg", "1.2.2")



Attach the package and use:
library("funreg")
Maintained by
John Dziak
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-06-21
Latest Update: 2021-10-04
Description:
Performs functional regression, and some related approaches, for intensive longitudinal data (see the book by Walls & Schafer, 2006, Models for Intensive Longitudinal Data, Oxford) when such data is not necessarily observed on an equally spaced grid of times. The approach generally follows the ideas of Goldsmith, Bobb, Crainiceanu, Caffo, and Reich (2011) and the approach taken in their sample code, but with some modifications to make it more feasible to use with long rather than wide, non-rectangular longitudinal datasets with unequal and potentially random measurement times. It also allows easy plotting of the correlation between the smoothed covariate and the outcome as a function of time, which can add additional insights on how to interpret a functional regression. Additionally, it also provides several permutation tests for the significance of the functional predictor. The heuristic interpretation of ``time'' is used to describe the index of the functional predictor, but the same methods can equally be used for another unidimensional continuous index, such as space along a north-south axis. Note that most of the functionality of this package has been superseded by added features after 2016 in the 'pfr' function by Jonathan Gellar, Mathew W. McLean, Jeff Goldsmith, and Fabian Scheipl, in the 'refund' package built by Jeff Goldsmith and co-authors and maintained by Julia Wrobel. The development of the funreg package in 2015 and 2016 was part of a research project supported by Award R03 CA171809-01 from the National Cancer Institute and Award P50 DA010075 from the National Institute on Drug Abuse. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse, the National Cancer Institute, or the National Institutes of Health.
How to cite:
John Dziak (2014). funreg: Functional Regression for Irregularly Timed Data. R package version 1.2.2, https://cran.r-project.org/web/packages/funreg. Accessed 07 Mar. 2026.
Previous versions and publish date:
1.1 (2014-06-21 01:11), 1.2 (2016-08-24 18:38)
Other packages that cited funreg R package
View funreg citation profile
Other R packages that funreg depends, imports, suggests or enhances
Complete documentation for funreg
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
portalr  
Create Useful Summaries of the Portal Data
Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Projec ...
Download / Learn more Package Citations See dependency  
testDriveR  
Teaching Data for Statistics and Data Science
Provides data sets for teaching statistics and data science courses. It includes a sample of data f ...
Download / Learn more Package Citations See dependency  
SAMtool  
Stock Assessment Methods Toolkit
Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform ...
Download / Learn more Package Citations See dependency  
ReviewR  
A Light-Weight, Portable Tool for Reviewing Individual Patient Records
A portable Shiny tool to explore patient-level electronic health record data and perform chart revi ...
Download / Learn more Package Citations See dependency  
lmSubsets  
Exact Variable-Subset Selection in Linear Regression
Exact and approximation algorithms for variable-subset selection in ordinary linear regression mode ...
Download / Learn more Package Citations See dependency  

26,264

R Packages

223,360

Dependencies

70,376

Author Associations

26,265

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA