Log-likelihood method for dfr_dist objects

Returns a function that computes the log-likelihood of the data given the distribution parameters. The log-likelihood for survival data is:

Usage

# S3 method for class 'dfr_dist'
loglik(model, ...)

Arguments

model

The dfr_dist object

...

Additional arguments to pass to the hazard and cumulative hazard

Value

A function that computes the log-likelihood. It accepts: - df: A data frame with observation times and censoring indicators (delta: 1 = exact, 0 = right-censored, -1 = left-censored) - par: The parameters of the distribution - ...: Additional arguments passed to internal functions

Details

For exact observations (uncensored): log(f(t)) = log(h(t)) - H(t) For right-censored observations: log(S(t)) = -H(t) For left-censored observations: log(F(t)) = log(1 - exp(-H(t)))

where h(t) is the hazard function, H(t) is the cumulative hazard, f(t) = h(t)*S(t) is the pdf, and S(t) = exp(-H(t)) is the survival function.