el_control | R Documentation |
Specifies computational details of (constrained) empirical likelihood.
el_control(
maxit = 200L,
maxit_l = 25L,
tol = 1e-06,
tol_l = 1e-06,
step = NULL,
th = NULL,
verbose = FALSE,
keep_data = TRUE,
nthreads,
seed = NULL,
an = NULL,
b = 10000L,
m = 1000000L
)
maxit |
A single integer for the maximum number of iterations for
constrained minimization of empirical likelihood. Defaults to |
maxit_l |
A single integer for the maximum number of iterations for
evaluation of empirical likelihood. Defaults to |
tol |
A single numeric for the convergence tolerance for the constrained
minimization. Defaults to |
tol_l |
A single numeric for the relative convergence tolerance for the
evaluation. Defaults to |
step |
A single numeric for the step size for projected gradient descent
method. Defaults to |
th |
A single numeric for the threshold for the negative empirical
log-likelihood ratio. The iteration stops if the value exceeds the
threshold. Defaults to |
verbose |
A single logical. If |
keep_data |
A single logical. If |
nthreads |
A single integer for the number of threads for parallel
computation via OpenMP (if available). Defaults to half the available
threads. For better performance, it is generally recommended in most
platforms to limit the number of threads to the number of physical cores.
Note that it applies to the following functions that involve multiple
evaluations or optimizations: |
seed |
A single integer for the seed for random number generation. It
only applies to |
an |
A single numeric representing the scaling factor for adjusted
empirical likelihood calibration. It only applies to |
b |
A single integer for the number of bootstrap replicates. It only
applies to |
m |
A single integer for the number of Monte Carlo samples. It only
applies to |
An object of class of ControlEL.
el_eval()
, elt()
optcfg <- el_control(maxit = 300, step = 0.01, th = 200, nthreads = 1)
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