logLik.bayesCureModel {bayesCureRateModel} | R Documentation |
Extract the log-likelihood.
Description
Method to extract the log-likelihood of a bayesCureModel
object.
Usage
## S3 method for class 'bayesCureModel'
logLik(object, ...)
Arguments
object |
An object of class |
... |
ignored. |
Value
The maximum (observed) log-likelihood value obtained across the MCMC run.
Author(s)
Panagiotis Papastamoulis
References
Papastamoulis and Milienos (2024). Bayesian inference and cure rate modeling for event history data. TEST doi: 10.1007/s11749-024-00942-w.
See Also
Examples
# simulate toy data just for cran-check purposes
set.seed(10)
n = 4
# censoring indicators
stat = rbinom(n, size = 1, prob = 0.5)
# covariates
x <- matrix(rnorm(2*n), n, 2)
# observed response variable
y <- rexp(n)
# define a data frame with the response and the covariates
my_data_frame <- data.frame(y, stat, x1 = x[,1], x2 = x[,2])
# run a weibull model with default prior setup
# considering 2 heated chains
fit1 <- cure_rate_MC3(survival::Surv(y, stat) ~ x1 + x2,
data = my_data_frame,
promotion_time = list(family = 'exponential'),
nChains = 2,
nCores = 1,
mcmc_cycles = 3, sweep=2)
ll <- logLik(fit1)
[Package bayesCureRateModel version 1.4 Index]