Package: hdcuremodels 0.0.6

Kellie J. Archer

hdcuremodels: High-Dimensional Cure Models

Provides functions for fitting various penalized parametric and semi-parametric mixture cure models with different penalty functions, testing for a significant cure fraction, and testing for sufficient follow-up as described in Fu et al (2022)<doi:10.1002/sim.9513> and Archer et al (2024)<doi:10.1186/s13045-024-01553-6>. False discovery rate controlled variable selection is provided using model-X knock-offs.

Authors:Han Fu [aut], Kellie J. Archer [aut, cre], Tung Lam Nguyen [rev], Panagiotis Papastamoulis [rev]

hdcuremodels_0.0.6.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
hdcuremodels/json (API)

# Install 'hdcuremodels' in R:
install.packages('hdcuremodels', repos = c('https://packages.ropensci.org', 'https://cloud.r-project.org'))

Reviews:rOpenSci Software Review #692

Bug tracker:https://github.com/ropensci/hdcuremodels/issues

Pkgdown/docs site:https://docs.ropensci.org

Datasets:

On CRAN:

Conda:

5.74 score 9 scripts 12k downloads 10 exports 106 dependencies

Last updated from:466902cdc6 (on main). Checks:4 OK, 6 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK341
pkgdown docsOK224
source / vignettesOK247
linux-release-x86_64ERROR399
macos-release-arm64ERROR273
macos-oldrel-arm64ERROR313
windows-develERROR365
windows-releaseERROR439
windows-oldrelERROR405
wasm-releaseOK191

Exports:auc_mcmconcordance_mcmcure_estimatecureemcuregmifscv_cureemcv_curegmifsgenerate_cure_datanonzerocure_testsufficient_fu_test

Dependencies:abindassertthatbackportsbbmlebdsmatrixBHbootbroomcarcarDataclicodetoolscolorspacecorpcorcorrplotcowplotcpp11data.tableDerivdeSolvedoBydoParalleldplyrfarverfastGHQuadflexsurvflexsurvcureforeachforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifglmnetgluegridExtragtablegtoolsisobanditeratorsknockofflabelinglatticelifecyclelme4lmtestlsodamagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmstatemuhazmvnfastmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolynompurrrquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackRdsdpreformulasrlangRSpectrarstatixrstpm2S7scalesshapeSparseMstatmodstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Estimating Cure Models in High Dimensions: A Guide with hdcuremodels

Rendered fromhdcuremodels.Rmdusingknitr::rmarkdownon May 17 2026.

Last update: 2025-09-12
Started: 2025-03-21

Readme and manuals

Help Manual

Help pageTopics
AML test dataamltest
AML training dataamltrain
AUC for cure prediction using mean score imputationauc_mcm
Extract model coefficients from a fitted mixturecure objectcoef.mixturecure coefficients
C-statistic for mixture cure modelsconcordance_mcm
Estimate cured fractioncure_estimate
Fit penalized mixture cure model using the E-M algorithmcureem
Fit penalized parametric mixture cure model using the GMIFS algorithmcuregmifs
Fit penalized mixture cure model using the E-M algorithm with cross-validation for parameter tuningcv_cureem
Fit a penalized parametric mixture cure model using the generalized monotone incremental forward stagewise (GMIFS) algorithm (Hastie et al 2007) with cross-validation for model selectioncv_curegmifs
Dimension method for mixturecure objectsdim.mixturecure
Return model family and fitting algorithm for mixturecure model fitsfamily.mixturecure
Extract model formula for mixturecure objectformula.mixturecure
Simulate data under a mixture cure modelgenerate_cure_data
Log-likelihood for fitted mixture cure modellogLik.mixturecure
Number of observations in mixturecure objectnobs.mixturecure
Non-parametric test for a non-zero cured fractionnonzerocure_test
Number of parameters in fitted mixture cure modelnpar_mixturecure
Pediatric acute myeloid leukemia patients with FLT3-ITD rearrangement datapediatric_flt3
Plot fitted mixture cure modelplot.mixturecure
Predicted probabilities for susceptibles, linear predictor for latency, and risk class for latency for mixture cure fitpredict.mixturecure
Print the contents of a mixture cure fitted objectprint.mixturecure
Test for sufficient follow-upsufficient_fu_test
Summarize a fitted mixture cure objectsummary.mixturecure