MLE fitting for masked-cause DFR series systems — fit.dfr_series

Returns a solver function that finds the maximum likelihood estimates for component parameters given masked series system data.

Usage

# S3 method for class 'dfr_series_md'
fit(object, ...)

Arguments

object: A dfr_series_md object.
...: Additional arguments (currently unused).

Value

A solver function with signature function(df, par, method = "Nelder-Mead", ..., control = list()) that returns a fisher_mle object.

Details

Uses optim to maximize the log-likelihood. The score function (gradient) is provided for gradient-based methods. The Hessian at the MLE is computed for variance-covariance estimation.