mixsurv: Mixture cure models

In flexsurvcure: Flexible Parametric Cure Models

Mixture cure models

Description

Probability density, distribution, quantile, random generation, hazard cumulative hazard, mean, and restricted mean functions for generic mixture cure models. These distribution functions take as arguments the corresponding functions of the base distribution used.

Usage

pmixsurv(pfun, q, theta, ...)

hmixsurv(dfun, pfun, x, theta, ...)

Hmixsurv(pfun, x, theta, ...)

dmixsurv(dfun, pfun, x, theta, ...)

qmixsurv(qfun, p, theta, ...)

rmixsurv(qfun, n, theta, ...)

rmst_mixsurv(pfun, t, theta, ...)

mean_mixsurv(pfun, theta, ...)

Arguments

pfun	The base distribution's cumulative distribution function.
theta	The estimated cure fraction.
...	additional parameters to be passed to the pdf or cdf of the base distribution.
dfun	The base distribution's probability density function.
x, q, t	Vector of times.
qfun	The base distribution's quantile function.
p	Vector of probabilities.
n	Number of random numbers to simulate.

Value

dmixsurv gives the density, pmixsurv gives the distribution function, hmixsurv gives the hazard and Hmixsurv gives the cumulative hazard.

qmixsurv gives the quantile function, which is computed by crude numerical inversion.

rmixsurv generates random survival times by using qmixsurv on a sample of uniform random numbers. Due to the numerical root-finding involved in qmixsurv, it is slow compared to typical random number generation functions.

mean_mixsurv and rmst_mixsurv give the mean and restricted mean survival times, respectively.

Author(s)

Jordan Amdahl <[e-mail]>

flexsurvcure documentation built on Nov. 2, 2022, 1:07 a.m.