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Introduction

fastcmprsk is an R package for performing Fine-Gray regression via a forward-backward scan algorithm.

Official CRAN release is available here.

NOTE TO USERS: We plan to make monthly/quarterly updates to the package!

What’s New in Version 1.24.10?

  1. Made modification to allow for more than one competing risk.

Features

  • Scalable Fine-Gray parameter estimation procedure for large-scale competing risks data.
  • Currently supports unpenalized and penalized (LASSO, ridge, SCAD, MCP, elastic-net) regression.
  • Can perform CIF estimation with interval/band estimation via bootstrap.

Implementation

fastcmprsk in an R package with most functionality implemented in C. The package uses cyclic coordinate descent to optimize the likelihood function.

Installation

To install the latest development version, install from GitHub.

install.packages("devtools")
devtools::install_github(“erickawaguchi/fastcmprsk”)

System Requirements

Requires R (version 4.4.0 or higher).

User Documentation

License

fastcmprsk is licensed under GPL-3.

Development

fastcmprsk is being developed in R Studio.

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Version

Install

install.packages('fastcmprsk')

Monthly Downloads

239

Version

1.26.1

License

GPL-3

Maintainer

Eric Kawaguchi

Last Published

February 25th, 2026

Functions in fastcmprsk (1.26.1)

plot.predict.fcrr

Plots predicted cumulative incidence function
plot.fcrrp

Plots solution path for penalized methods
print.summary.fcrr

Prints summary of a fcrr x
predict.fcrr

Cumulative Incidence Function Estimation
AIC.fcrr

Akaike's An Information Criterion
logLik.fcrr

Extract log-pseudo likelihood from an "fcrr" object.
Crisk

Create a Competing Risk Object
confint.fcrr

Confidence Intervals for Model Parameters
coef.fcrrp

Extract coefficients from an "fcrrp" object.
AIC.fcrrp

Akaike's An Information Criterion
coef.fcrr

Extract coefficients from an "fcrr" object.
logLik.fcrrp

Extract log-pseudo likelihood from an "fcrrp" object.
fastCrrp

Penalized Fine-Gray Model Estimation via two-way linear scan
vcov.fcrr

Extract variance-covariance matrix from an "fcrr" object.
varianceControl

Controls for Variance Calculation
fastCrr

Fast Fine-Gray Model Estimation
simulateTwoCauseFineGrayModel

Simulate data from the Fine-Gray Model
summary.fcrr

Summary method for fastCrr