reg_control: Tuning parameters for MM-regression

Description Usage Arguments Value Note Author(s) References See Also Examples

View source: R/control.R

Description

Obtain a list with tuning paramters for lmrob.

Usage

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

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).

Value

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

Note

This is a simplified wrapper function for lmrob.control, as the latter requires detailed knowledge of the MM-type regression algorithm. Currently only 95%, 90%, 85% (the default) and 80% efficiency are supported. For other values, please specify the corresponding tuning parameters in lmrob.control directly.

Author(s)

Andreas Alfons

References

Salibian-Barrera, M. and Yohai, V.J. (1987) A fast algorithm for S-regression estimates. Journal of Computational and Graphical Statistics, 15(2), 414–427.

Yohai, V.J. (1987) High breakdown-point and high efficiency estimates for regression. The Annals of Statistics, 15(20), 642–656.

See Also

lmrob, lmrob.control

Examples

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data("BSG2014")

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

robmed documentation built on Nov. 5, 2018, 5:06 p.m.