# mixsurv: Mixture cure models In flexsurvcure: Flexible Parametric 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```pmixsurv(pfun, q, theta, ...) hmixsurv(dfun, pfun, x, theta, ...) Hmixsurv(pfun, x, theta, ...) dmixsurv(dfun, pfun, x, theta, ...) qmixsurv(pfun, p, theta, ...) rmixsurv(pfun, 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. `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 <[email protected]>

flexsurvcure documentation built on July 17, 2017, 9:02 a.m.