Package: incubate 1.4.0

incubate: Parametric Time-to-Event Analysis with Variable Incubation Phases

Fit parametric models for time-to-event data that show an initial 'incubation period', i.e., a variable delay phase where no events occur. The delayed Weibull distribution serves as the foundational data model. For parameter estimation, different flavours of maximum likelihood estimation ('MLE') and the method of maximum product of spacings estimation ('MPSE') are implemented. Bootstrap confidence intervals for parameters and significance tests in a two group setting are provided.

Authors:Matthias Kuhn [aut, cre, cph]

incubate_1.4.0.tar.gz
incubate_1.4.0.zip(r-4.7)incubate_1.4.0.zip(r-4.6)incubate_1.4.0.zip(r-4.5)
incubate_1.4.0.tgz(r-4.6-x86_64)incubate_1.4.0.tgz(r-4.6-arm64)incubate_1.4.0.tgz(r-4.5-x86_64)incubate_1.4.0.tgz(r-4.5-arm64)
incubate_1.4.0.tar.gz(r-4.7-arm64)incubate_1.4.0.tar.gz(r-4.7-x86_64)incubate_1.4.0.tar.gz(r-4.6-arm64)incubate_1.4.0.tar.gz(r-4.6-x86_64)
incubate_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
incubate/json (API)
NEWS

# Install 'incubate' in R:
install.packages('incubate', repos = c('https://lenz99.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://gitlab.com/imb-dev/incubate

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • fatigue - Small data sets from miscellaneous publications
  • graphite - Small data sets from miscellaneous publications
  • long2017 - Relapse-free survival of melanoma patients under adjuvant treatment
  • measles_sailer - Serial interval times for measles during a long journey on a sailing vessel
  • pollution - Small data sets from miscellaneous publications
  • rockette - Small data sets from miscellaneous publications
  • rockette74 - Small data sets from miscellaneous publications
  • stankovic - Survival time of mice with glioma under different treatments
  • susquehanna - Small data sets from miscellaneous publications

On CRAN:

Conda:

cpp

4.48 score 205 downloads 15 exports 25 dependencies

Last updated from:118a189356. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK245
linux-devel-x86_64OK282
source / vignettesOK204
linux-release-arm64OK247
linux-release-x86_64OK254
macos-release-arm64OK179
macos-release-x86_64OK395
macos-oldrel-arm64OK283
macos-oldrel-x86_64OK354
windows-develOK237
windows-releaseOK228
windows-oldrelOK256
wasm-releaseOK120

Exports:buildDistdelay_modeldexp_delayeddweib_delayedmexp_delayedmweib_delayedpexp_delayedpower_diffpweib_delayedqexp_delayedqweib_delayedrexp_delayedrweib_delayedtest_difftest_GOF

Dependencies:clicodetoolscpp11digestfuturefuture.applyglobalsgluelatticelifecyclelistenvmagrittrMASSMatrixminqaparallellypillarpkgconfigpurrrRcpprlangsurvivaltibbleutf8vctrs

Distributions with Delay

[email protected]

Rendered fromdelayed-dist.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2025-09-08
Started: 2024-08-16

Readme and manuals

Help Manual

Help pageTopics
Format a number as percentage.as_percent
Generate bootstrap distribution of model parameters to fitted incubate model.bsDataStep
Build control list for 'delay_model()' and 'objFunFactory()'buildControl
Builds the distribution objectbuildDist
Coefficients of a delay-model fit.coef.incubate_fit
Confidence intervals for parameters of incubate-model fits.confint.incubate_fit
Fit optimal parameters according to the objective function (either MPSE or MLE-based).delay_fit
Fit a delayed Exponential or Weibull model to one or two given sample(s)delay_model
Delayed Exponential DistributionDelayedExponential dexp_delayed mexp_delayed pexp_delayed qexp_delayed rexp_delayed
Delayed Weibull DistributionDelayedWeibull dweib_delayed mweib_delayed pweib_delayed qweib_delayed rweib_delayed
Estimate rounding error based on given sample of metric values The idea is to check at which level of rounding the sample values do not change.estimRoundingError
Get delay distribution functiongetDist
Add a line fit to a plot of (another) 'incubate_fit' objectlines.incubate_fit
Extract Log-LikelihoodlogLik.incubate_fit
Relapse-free survival of melanoma patients under adjuvant treatmentlong2017
Serial interval times for measles during a long journey on a sailing vesselmeasles_sailer
Minimize an objective function with alternative optimizerminObjFunAlt
Checks if arguments are numerically close.near
Factory method for objective functionobjFunFactory
Plot a fitted delay-model object of class 'incubate_fit'plot.incubate_fit
Power simulation function for a two-group comparisonpower_diff
Check and prepare the survival response(s)prepResponseVar
Small data sets from miscellaneous publicationsfatigue graphite pollution rockette rockette74 susquehanna
Calculate parameter scaling for optimization routine.scalePars
Survival time of mice with glioma under different treatmentsstankovic
Test the difference for model parameter(s) between two uncorrelated groupstest_diff
Goodness-of-fit (GOF) test statistic (experimental!)test_GOF
Transform observed data to unit intervaltransform.incubate_fit
Refit an 'incubate_fit'-object with specified optimization argumentsupdate.incubate_fit
Internal MLEw-weight W1 function according to sampling distribution Weight W1 for given sample sizes (of one group). For small 'nObs' we use direct results from Monte-Carlo simulation. For higher 'nObs' we use an approximation (based on Wilson-Hilferty transformation).w1Fint
Internal MLEw weight function W2 according to sampling distribution W2 is either taken directly from the MCSS-results (if available) or are taken from the smooth approximation function, otherwise.w2Fint
Internal factory method for W3-function based on sampling distributionw3FFint