hdcuremodels (version 0.0.6)

logLik.mixturecure: Log-likelihood for fitted mixture cure model

Description

This function returns the log-likelihood for a user-specified model criterion or step for a curegmifs, cureem, cv_curegmifs or cv_cureem fitted object.

Usage

# S3 method for mixturecure
logLik(object, model_select = "AIC", ...)

Value

log-likelihood of the fitted mixture cure model using the specified criteria.

Arguments

object

a mixturecure object resulting from curegmifs, cureem, cv_curegmifs, cv_cureem.

model_select

either a case-sensitive parameter for models fit using curegmifs or cureem or any numeric step along the solution path can be selected. The default is model_select = "AIC" which calculates the predicted values using the coefficients from the model achieving the minimum AIC. The complete list of options are:

• "AIC" for the minimum AIC (default).

• "mAIC" for the minimum modified AIC.

• "cAIC" for the minimum corrected AIC.

• "BIC", for the minimum BIC.

• "mBIC" for the minimum modified BIC.

• "EBIC" for the minimum extended BIC.

• "logLik" for the step that maximizes the log-likelihood.

• n where n is any numeric value from the solution path.

This option has no effect for objects fit using cv_curegmifs or cv_cureem.

...

other arguments.

Examples

library(survival)
withr::local_seed(1234)
temp <- generate_cure_data(n = 100, j = 10, n_true = 10, a = 1.8)
training <- temp$training
fit <- curegmifs(Surv(Time, Censor) ~ .,
  data = training, x_latency = training,
  model = "weibull", thresh = 1e-4, maxit = 2000,
  epsilon = 0.01, verbose = FALSE
)
logLik(fit, model_select = "AIC")