Description Usage Arguments Value References Examples
Rank the features by selected percentages provided by the output from RaScreen
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1  RaRank(object, selected.num = "all positive", iteration = object$iteration)

object 
output from 
selected.num 
the number of selected variables. User can either choose from the following popular options or input an positive integer no larger than the dimension.

iteration 
indicates results from which iteration to use. It should be an positive integer. Default = the maximal interation round used by the output from 
Selected variables (indexes).
Tian, Y. and Feng, Y., 2021(a). RaSE: A variable screening framework via random subspace ensembles. Journal of the American Statistical Association, (justaccepted), pp.130.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  ## Not run:
set.seed(0, kind = "L'EcuyerCMRG")
train.data < RaModel("screening", 1, n = 100, p = 100)
xtrain < train.data$x
ytrain < train.data$y
# test RaSE screening with linear regression model and BIC
fit < RaScreen(xtrain, ytrain, B1 = 100, B2 = 50, iteration = 0, model = 'lm',
cores = 2, criterion = 'bic')
# Select floor(n/logn) variables
RaRank(fit, selected.num = "n/logn")
## End(Not run)

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