This function defines auxiliary parameters that control the model fitting process.
fit.control(
toll = 1e-04,
h = 1,
it.max = 50,
K.max = 6,
stop.if.error = TRUE,
dev0 = NULL,
visual = FALSE,
visualBoot = FALSE,
pow = c(1, 1),
digits = NULL,
grid = NULL,
n.boot = 20
)
A list with the arguments as components to be used by mkqr.fit and mkqr.bea.
Positive convergence tolerance.
Positive factor (from zero to one) modifying the increments in kink parameter updates during the iterative process.
Positive integer for the maximal number of iterations.
Positive integer for the maximal given number of kink points.
Logical indicating if the estimation algorithm should be stopped if some kink point estimators belong to the non-admissible set. Default is FALSE which suggests removing the non-admissible change points automatically.
Initial objective value or deviance. Default is NULL which implies that the initial value is unknown.
Logical indicating if the results of the estimation process should be printed at each iteration.
Logical indicating if the results of estimation should be printed at each iteration in the bootstrap restarting process.
The powers of the pseudo covariates employed by the algorithm.
If specified, it means the desired number of decimal points of the kink estimators to be used during the iterative algorithm.
It measures how close between the two adjacent change points should be merged, default is NULL.
Positive integer indicating the times of bootstrap re-sampling in the bootstrap restarting algorithm, default is 20.
# Example usage
fit.control(K.max=8)
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