robmed (version 1.0.0)

reg_control: Tuning parameters for MM-regression

Description

Obtain a list with tuning paramters for lmrob().

Usage

reg_control(efficiency = 0.85, max_iterations = 200, tol = 1e-07, seed = NULL)

Value

A list of tuning parameters as returned by lmrob.control().

Arguments

efficiency

a numeric value giving the desired efficiency (defaults to 0.85 for 85% efficiency).

max_iterations

an integer giving the maximum number of iterations in various parts of the algorithm.

tol

a small positive numeric value to be used to determine convergence in various parts of the algorithm.

seed

optional initial seed for the random number generator (see .Random.seed).

Author

Andreas Alfons

References

Salibian-Barrera, M. and Yohai, V.J. (2006) A Fast Algorithm for S-regression Estimates. Journal of Computational and Graphical Statistics, 15(2), 414--427. doi:10.1198/106186006x113629.

Yohai, V.J. (1987) High Breakdown-Point and High Efficiency Estimates for Regression. The Annals of Statistics, 15(20), 642--656. doi:10.1214/aos/1176350366.

See Also

lmrob(), lmrob.control()

Examples

data("BSG2014")

# run fast-and-robust bootstrap test
ctrl <- reg_control(efficiency = 0.95)
boot <- test_mediation(BSG2014,
                       x = "ValueDiversity",
                       y = "TeamCommitment",
                       m = "TaskConflict",
                       control = ctrl)
summary(boot)