flexsurvreg objects are created from the flexsurv package. They differ from survreg in that the fitted models are not limited to certain parametric distributions. Users can define their own distribution, or leverage distributions like the generalized gamma, generalized F, and the Royston-Parmar spline model.

# S3 method for flexsurvreg
axe_call(x, verbose = FALSE, ...)

# S3 method for flexsurvreg
axe_env(x, verbose = FALSE, ...)

Arguments

x

A model object.

verbose

Print information each time an axe method is executed. Notes how much memory is released and what functions are disabled. Default is FALSE.

...

Any additional arguments related to axing.

Value

Axed flexsurvreg object.

Examples

# \donttest{ # Load libraries suppressWarnings(suppressMessages(library(parsnip))) suppressWarnings(suppressMessages(library(flexsurv))) # Create model and fit flexsurvreg_fit <- surv_reg(mode = "regression", dist = "gengamma") %>% set_engine("flexsurv") %>% fit(Surv(Tstart, Tstop, status) ~ trans, data = bosms3) out <- butcher(flexsurvreg_fit, verbose = TRUE)
#> Memory released: '2,376 B'
# Another flexsurvreg model object wrapped_flexsurvreg <- function() { some_junk_in_environment <- runif(1e6) fit <- flexsurvreg(Surv(futime, fustat) ~ 1, data = ovarian, dist = "weibull") return(fit) } out <- butcher(wrapped_flexsurvreg(), verbose = TRUE)
#> Memory released: '8,190,552 B'
#> Disabled: `print()`
# }