Package: incubate 1.4.1

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_1.4.1.tar.gz
incubate_1.4.1.zip(r-4.7)incubate_1.4.1.zip(r-4.6)incubate_1.4.1.zip(r-4.5)
incubate_1.4.1.tgz(r-4.6-x86_64)incubate_1.4.1.tgz(r-4.6-arm64)incubate_1.4.1.tgz(r-4.5-x86_64)incubate_1.4.1.tgz(r-4.5-arm64)
incubate_1.4.1.tar.gz(r-4.7-arm64)incubate_1.4.1.tar.gz(r-4.7-x86_64)incubate_1.4.1.tar.gz(r-4.6-arm64)incubate_1.4.1.tar.gz(r-4.6-x86_64)
incubate_1.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
incubate/json (API)

# 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:

cpp

4.54 score 3 scripts 196 downloads 15 exports 25 dependencies

Last updated from:4a5addb527. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	261
linux-devel-x86_64	OK	343
source / vignettes	OK	332
linux-release-arm64	OK	275
linux-release-x86_64	OK	268
macos-release-arm64	OK	260
macos-release-x86_64	OK	370
macos-oldrel-arm64	OK	212
macos-oldrel-x86_64	OK	361
windows-devel	OK	191
windows-release	OK	269
windows-oldrel	OK	244
wasm-release	OK	121

Exports:buildDist delay_model dexp_delayed dweib_delayed mexp_delayed mweib_delayed pexp_delayed power_diff pweib_delayed qexp_delayed qweib_delayed rexp_delayed rweib_delayed test_diff test_GOF

Dependencies:cli codetools cpp11 digest future future.apply globals glue lattice lifecycle listenv magrittr MASS Matrix minqa parallelly pillar pkgconfig purrr Rcpp rlang survival tibble utf8 vctrs

Distributions with Delay

Rendered fromdelayed-dist.Rmdusingknitr::rmarkdown

Last update: 2026-06-04
Started: 2024-08-16

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Format a number as percentage.	as_percent
Generate bootstrap distribution of model parameters to a fitted incubate model	bsDataStep
Build control list for 'delay_model()' and 'objFunFactory()'	buildControl
Builds the distribution object	buildDist
Coefficients of a delay-model fit.	coef.incubate_fit
Confidence intervals for parameters of delay model fit	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 Distribution	DelayedExponential dexp_delayed mexp_delayed pexp_delayed qexp_delayed rexp_delayed
Delayed Weibull Distribution	DelayedWeibull 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 function	getDist
Get the standard deviation of the fitted delay model fit	getVariance
Add a line fit to a plot of (another) 'incubate_fit' object	lines.incubate_fit
Extract Log-Likelihood	logLik.incubate_fit
Relapse-free survival of melanoma patients under adjuvant treatment	long2017
Serial interval times for measles during a long journey on a sailing vessel	measles_sailer
Minimize an objective function with alternative optimizer	minObjFunAlt
Checks if arguments are numerically close.	near
Factory method for objective function	objFunFactory
Plot a fitted delay-model object of class 'incubate_fit'	plot.incubate_fit
Power simulation function for a two-group comparison	power_diff
Check and prepare the survival response(s)	prepResponseVar
Small data sets from miscellaneous publications	fatigue graphite pollution rockette rockette74 susquehanna
Calculate parameter scaling for optimization routine.	scalePars
Survival time of mice with glioma under different treatments	stankovic
Test the difference for model parameter(s) between two uncorrelated groups	test_diff
Goodness-of-fit (GOF) test statistic (experimental!)	test_GOF
Transform observed data to unit interval	transform.incubate_fit
Refit an 'incubate_fit'-object with specified optimization arguments	update.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 distribution	w3FFint