library("robustbase")
data("coleman")
## evaluate MM regression models tuned for 85% and 95% efficiency
tuning <- list(tuning.psi = c(3.443689, 4.685061))
## via model fitting function
# perform cross-validation
# note that the response is extracted from 'data' in
# this example and does not have to be supplied
cvTuning(lmrob, formula = Y ~ ., data = coleman, tuning = tuning,
cost = rtmspe, K = 5, R = 10, costArgs = list(trim = 0.1),
seed = 1234)
## via function call
# set up function call
call <- call("lmrob", formula = Y ~ .)
# perform cross-validation
cvTuning(call, data = coleman, y = coleman$Y, tuning = tuning,
cost = rtmspe, K = 5, R = 10, costArgs = list(trim = 0.1),
seed = 1234)
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