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bayesCureRateModel (version 1.5)

logLik.bayesCureModel: Extract the log-likelihood.

Description

Method to extract the log-likelihood of a bayesCureModel object.

Usage

# S3 method for bayesCureModel
logLik(object, ...)

Value

The maximum (observed) log-likelihood value obtained across the MCMC run.

Arguments

object

An object of class bayesCureModel

...

ignored.

Author

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

Run this code
# 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)

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