S4 class for computational details of empirical likelihood.
maxitA single integer for the maximum number of iterations for the optimization with respect to \(\theta\).
maxit_lA single integer for the maximum number of iterations for the optimization with respect to \(\lambda\).
tolA single numeric for the convergence tolerance denoted by \(\epsilon\). The iteration stops when $$\|P \nabla l(\theta^{(k)})\| < \epsilon.$$
tol_lA single numeric for the relative convergence tolerance denoted by \(\delta\). The iteration stops when $$\|\lambda^{(k)} - \lambda^{(k - 1)}\| < \delta\|\lambda^{(k - 1)}\| + \delta^2.$$
stepA single numeric for the step size \(\gamma\) for the projected gradient descent method.
thA single numeric for the threshold for the negative empirical log-likelihood ratio.
verboseA single logical for whether to print a message on the convergence status.
keep_dataA single logical for whether to keep the data used for fitting model objects.
nthreadsA single integer for the number of threads for parallel computation via OpenMP (if available).
seedA single integer for the seed for random number generation.
anA single numeric representing the scaling factor for adjusted empirical likelihood calibration.
bA single integer for the number of bootstrap replicates.
mA single integer for the number of Monte Carlo samples.
showClass("ControlEL")
#> Class "ControlEL" [package "melt"]
#>
#> Slots:
#>
#> Name: maxit maxit_l tol tol_l step th verbose
#> Class: integer integer numeric numeric ANY ANY logical
#>
#> Name: keep_data nthreads seed an b m
#> Class: logical integer ANY ANY integer integer