Perform AIC forward selection for nrm.
nrm_selection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... )# S3 method for default nrm_selection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... )# S3 method for nrmpredictor nrm_selection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... )# S3 method for nrm_selection print(x, ...)
# S3 method for default nrm_selection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... )
# S3 method for nrmpredictor nrm_selection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... )
# S3 method for nrm_selection print(x, ...)
the adjacency matrix of the response network
list containing the set of predictors as sublists.
logical, is the response network directed?
logical, do the response network allows selfloops?
the significance at which computing confidence intervals.
optional, the possibility matrix \(\Xi\).
optional, initial values passed to the solver to estimate the MLE.
optional, number of cores over which parallelise the task.
optional arguments to print or plot methods.
object of class 'nrm_selection'.
'nrm_selection'
A nrm object
default: Default method for the nrm stepwise selection.
default
nrmpredictor: Method for the nrm stepwise selection when nrmpredictors are passed.
nrmpredictor
nrm_selection: Print method for elements of class 'nrm_selection'.
nrm_selection
nrm
# NOT RUN { data('highschool.predictors') nrm_selection(adj=contacts.adj,predictors=createPredictors(highschool.predictors), ncores=1,directed=FALSE,selfloops=FALSE) # }
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