Package: FunSurv 1.0.0

Zifang Kong

FunSurv: Modeling Time-to-Event Data with Functional Predictors

A collection of methods for modeling time-to-event data using both functional and scalar predictors. It implements functional data analysis techniques for estimation and inference, allowing researchers to assess the impact of functional covariates on survival outcomes, including time-to-single event and recurrent event outcomes.

Authors:Zifang Kong [aut, cre], Sy Han Chiou [aut], Yu-Lun Liu [aut]

FunSurv_1.0.0.tar.gz
FunSurv_1.0.0.zip(r-4.5)FunSurv_1.0.0.zip(r-4.4)FunSurv_1.0.0.zip(r-4.3)
FunSurv_1.0.0.tgz(r-4.5-any)FunSurv_1.0.0.tgz(r-4.4-any)FunSurv_1.0.0.tgz(r-4.3-any)
FunSurv_1.0.0.tar.gz(r-4.5-noble)FunSurv_1.0.0.tar.gz(r-4.4-noble)
FunSurv_1.0.0.tgz(r-4.4-emscripten)FunSurv_1.0.0.tgz(r-4.3-emscripten)
FunSurv.pdf |FunSurv.html✨
FunSurv/json (API)
NEWS

# Install 'FunSurv' in R:
install.packages('FunSurv', repos = c('https://zifangkong.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zifangkong/funsurv/issues

Datasets:
  • fdat - Simulated datasets for demonstration
  • sdat - Simulated datasets for demonstration

On CRAN:

Conda:

3.40 score 9 exports 44 dependencies

Last updated 15 days agofrom:303a3caca7. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 18 2025
R-4.5-winOKMar 18 2025
R-4.5-macOKMar 18 2025
R-4.5-linuxOKMar 18 2025
R-4.4-winOKMar 18 2025
R-4.4-macOKMar 18 2025
R-4.4-linuxOKMar 18 2025
R-4.3-winOKMar 18 2025
R-4.3-macOKMar 18 2025

Exports:%2%%to%ar1_corAR1_FRAILTYbasesurvcheck_Recurdar1_cor.drhois.RecurRecur

Dependencies:abindclicodetoolscolorspacedotCall64fansifarverfieldsforeachfunDataggplot2gluegtableirlbaisobanditeratorslabelinglatticelifecyclemagrittrmapsMASSMatrixMFPCAmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloredarlangscalesspamsplines2tibbleutf8vctrsviridisLitewithr