Function reference • flexsurv

All functions
`dgenf()` `pgenf()` `Hgenf()` `hgenf()` `qgenf()` `rgenf()`	Generalized F distribution
`dgenf.orig()` `pgenf.orig()` `Hgenf.orig()` `hgenf.orig()` `qgenf.orig()` `rgenf.orig()`	Generalized F distribution (original parameterisation)
`dgengamma()` `pgengamma()` `Hgengamma()` `hgengamma()` `qgengamma()` `rgengamma()`	Generalized gamma distribution
`dgengamma.orig()` `pgengamma.orig()` `Hgengamma.orig()` `hgengamma.orig()` `qgengamma.orig()` `rgengamma.orig()`	Generalized gamma distribution (original parameterisation)
`dgompertz()` `pgompertz()` `qgompertz()` `rgompertz()` `hgompertz()` `Hgompertz()`	The Gompertz distribution
`Llogis`	The log-logistic distribution
`dsurvspline()` `psurvspline()` `qsurvspline()` `rsurvspline()` `Hsurvspline()` `hsurvspline()` `rmst_survspline()` `mean_survspline()`	Royston/Parmar spline survival distribution
`mean_survspline0()` `mean_survspline1()` `mean_survspline2()` `mean_survspline3()` `mean_survspline4()` `mean_survspline5()` `mean_survspline6()` `mean_survspline7()` `rmst_survspline0()` `rmst_survspline1()` `rmst_survspline2()` `rmst_survspline3()` `rmst_survspline4()` `rmst_survspline5()` `rmst_survspline6()` `rmst_survspline7()` `dsurvspline0()` `dsurvspline1()` `dsurvspline2()` `dsurvspline3()` `dsurvspline4()` `dsurvspline5()` `dsurvspline6()` `dsurvspline7()` `psurvspline0()` `psurvspline1()` `psurvspline2()` `psurvspline3()` `psurvspline4()` `psurvspline5()` `psurvspline6()` `psurvspline7()` `qsurvspline0()` `qsurvspline1()` `qsurvspline2()` `qsurvspline3()` `qsurvspline4()` `qsurvspline5()` `qsurvspline6()` `qsurvspline7()` `rsurvspline0()` `rsurvspline1()` `rsurvspline2()` `rsurvspline3()` `rsurvspline4()` `rsurvspline5()` `rsurvspline6()` `rsurvspline7()` `hsurvspline0()` `hsurvspline1()` `hsurvspline2()` `hsurvspline3()` `hsurvspline4()` `hsurvspline5()` `hsurvspline6()` `hsurvspline7()` `Hsurvspline0()` `Hsurvspline1()` `Hsurvspline2()` `Hsurvspline3()` `Hsurvspline4()` `Hsurvspline5()` `Hsurvspline6()` `Hsurvspline7()`	Royston/Parmar spline survival distribution functions
`WeibullPH`	Weibull distribution in proportional hazards parameterisation
`ajfit()`	Aalen-Johansen nonparametric estimates comparable to a fitted flexsurvmix model
`ajfit_flexsurvmix()`	Forms a tidy data frame for plotting the fit of parametric mixture multi-state models against nonparametric estimates
`ajfit_fmsm()`	Check the fit of Markov flexible parametric multi-state models against nonparametric estimates.
`augment(<flexsurvreg>)`	Augment data with information from a flexsurv model object
`basis()`	Natural cubic spline basis
`bc`	Breast cancer survival data
`bootci.fmsm()`	Bootstrap confidence intervals for flexsurv output functions
`bos`	Bronchiolitis obliterans syndrome after lung transplants
`coef(<flexsurvreg>)`	Extract model coefficients from fitted flexible survival models
`flexsurv-package`	flexsurv: Flexible parametric survival and multi-state models
`flexsurvmix()`	Flexible parametric mixture models for times to competing events
`flexsurvreg()`	Flexible parametric regression for time-to-event data
`flexsurvrtrunc()`	Flexible parametric models for right-truncated, uncensored data defined by times of initial and final events.
`flexsurvspline()`	Flexible survival regression using the Royston/Parmar spline model.
`fmixmsm()`	Constructor for a mixture multi-state model based on flexsurvmix
`fmsm()`	Construct a multi-state model from a set of parametric survival models
`get_basepars()`	Evaluate baseline time-to-event distribution parameters given covariate values in a flexsurvmix model
`glance(<flexsurvreg>)`	Glance at a flexsurv model object
`hexp()` `Hexp()` `hgamma()` `Hgamma()` `hlnorm()` `Hlnorm()` `hweibull()` `Hweibull()`	Hazard and cumulative hazard functions
`lines(<flexsurvreg>)`	Add fitted flexible survival curves to a plot
`mean_flexsurvmix()`	Mean times to events from a flexsurvmix model
`meanfinal_fmixmsm()`	Mean time to final state in a mixture multi-state model
`mean_exp()` `rmst_exp()` `mean_gamma()` `rmst_gamma()` `rmst_genf()` `mean_genf()` `rmst_genf.orig()` `mean_genf.orig()` `rmst_gengamma()` `mean_gengamma()` `rmst_gengamma.orig()` `mean_gengamma.orig()` `rmst_gompertz()` `mean_gompertz()` `mean_lnorm()` `rmst_lnorm()` `mean_weibull()` `rmst_weibull()`	Mean and restricted mean survival functions
`model.frame(<flexsurvreg>)` `model.matrix(<flexsurvreg>)`	Extract original data from `flexsurvreg` objects.
`msfit.flexsurvreg()`	Cumulative intensity function for parametric multi-state models
`nobs(<flexsurvreg>)`	Number of observations contributing to a fitted flexible survival model
`normboot.flexsurvreg()`	Simulate from the asymptotic normal distribution of parameter estimates.
`p_flexsurvmix()`	Transition probabilities from a flexsurvmix model
`pars.fmsm()`	Transition-specific parameters in a flexible parametric multi-state model
`pdf_flexsurvmix()`	Fitted densities for times to events in a flexsurvmix model
`pfinal_fmsm()`	Probabilities of final states in a flexible parametric competing risks model
`plot(<flexsurvreg>)`	Plots of fitted flexible survival models
`plot(<survrtrunc>)` `lines(<survrtrunc>)`	Plot nonparametric estimates of survival from right-truncated data.
`pmatrix.fs()`	Transition probability matrix from a fully-parametric, time-inhomogeneous Markov multi-state model
`pmatrix.simfs()`	Transition probability matrix from a fully-parametric, semi-Markov multi-state model
`ppath_fmixmsm()`	Probability of each pathway taken through a mixture multi-state model
`predict(<flexsurvreg>)`	Predictions from flexible survival models
`probs_flexsurvmix()`	Probabilities of competing events from a flexsurvmix model
`qfinal_fmixmsm()`	Quantiles of the distribution of the time until reaching a final state in a mixture multi-state model
`qgeneric()`	Generic function to find quantiles of a distribution
`quantile_flexsurvmix()`	Quantiles of time-to-event distributions in a flexsurvmix model
`residuals(<flexsurvreg>)`	Calculate residuals for flexible survival models
`rmst_flexsurvmix()`	Restricted mean times to events from a flexsurvmix model
`rmst_generic()`	Generic function to find restricted mean survival of a distribution
`sim.fmsm()`	Simulate paths through a fully parametric semi-Markov multi-state model
`simfinal_fmsm()`	Simulate and summarise final outcomes from a flexible parametric multi-state model
`simfs_bytrans()`	Reformat simulated multi-state data with one row per simulated transition
`simt_flexsurvmix()`	Simulate times to competing events from a mixture multi-state model
`summary(<flexsurvreg>)`	Summaries of fitted flexible survival models
`summary(<flexsurvrtrunc>)`	Summarise quantities of interest from fitted flexsurvrtrunc models
`survrtrunc()`	Nonparametric estimator of survival from right-truncated, uncensored data
`tidy(<flexsurvreg>)`	Tidy a flexsurv model object
`totlos.fs()`	Total length of stay in particular states for a fully-parametric, time-inhomogeneous Markov multi-state model
`totlos.simfs()`	Expected total length of stay in specific states, from a fully-parametric, semi-Markov multi-state model
`unroll.function()`	Convert a function with matrix arguments to a function with vector arguments.

Reference

All functions