S4 class for computational details of empirical likelihood.

Slots

maxit

A single integer for the maximum number of iterations for the optimization with respect to \(\theta\).

maxit_l

A single integer for the maximum number of iterations for the optimization with respect to \(\lambda\).

tol

A single numeric for the convergence tolerance denoted by \(\epsilon\). The iteration stops when $$\|P \nabla l(\theta^{(k)})\| < \epsilon.$$

tol_l

A single numeric for the relative convergence tolerance denoted by \(\delta\). The iteration stops when $$\|\lambda^{(k)} - \lambda^{(k - 1)}\| < \delta\|\lambda^{(k - 1)}\| + \delta^2.$$

step

A single numeric for the step size \(\gamma\) for the projected gradient descent method.

th

A single numeric for the threshold for the negative empirical log-likelihood ratio.

verbose

A single logical for whether to print a message on the convergence status.

keep_data

A single logical for whether to keep the data used for fitting model objects.

nthreads

A single integer for the number of threads for parallel computation via OpenMP (if available).

seed

A single integer for the seed for random number generation.

an

A single numeric representing the scaling factor for adjusted empirical likelihood calibration.

b

A single integer for the number of bootstrap replicates.

m

A single integer for the number of Monte Carlo samples.

Examples

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