logLik.bayesCureModel: Extract the log-likelihood.

In bayesCureRateModel: Bayesian Cure Rate Modeling for Time-to-Event Data

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 bayesCureModel
...	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

cure_rate_MC3

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(distribution = 'exponential'),
		nChains = 2, 
		nCores = 1, 
		mcmc_cycles = 3, sweep=2)
	ll <- logLik(fit1)

bayesCureRateModel documentation built on Oct. 4, 2024, 1:07 a.m.