nrm_selection.Rd
Perform AIC forward selection for nrm.
nrmSelection( adj, predictors, directed, selfloops, pval = 0.05, xi = NULL, init = NULL, ncores = NULL, ... ) 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, ...)
adj | the adjacency matrix of the response network |
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predictors | list containing the set of predictors as sublists. |
directed | logical, is the response network directed? |
selfloops | logical, do the response network allows selfloops? |
pval | the significance at which computing confidence intervals. |
xi | optional, the possibility matrix \(\Xi\). |
init | optional, initial values passed to the solver to estimate the MLE. |
ncores | optional, number of cores over which parallelise the task. |
... | optional arguments to print or plot methods. |
x | object of class |
A nrm object
default
: Default method for the nrm stepwise selection.
nrmpredictor
: Method for the nrm stepwise selection when nrmpredictors are passed.
nrm_selection
: Print method for elements of class 'nrm_selection'
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nrm_selection
Giona Casiraghi
Giona Casiraghi
# \donttest{ data('highschool.predictors') models <- nrm_selection(adj=contacts.adj,predictors=create_predictors(highschool.predictors), ncores=1,directed=FALSE,selfloops=FALSE)#>#> #>#> #>#> #>#> #>#> #>#> #>#> #>#> #>#> #> ============================================================================================== #> Model 1 Model 2 Model 3 Model 4 Model 5 #> ---------------------------------------------------------------------------------------------- #> class 2.016 *** 1.914 *** 1.391 *** 1.393 *** 1.392 *** #> (0.004) (0.004) (0.005) (0.005) (0.005) #> friendship 0.679 *** 0.675 *** 0.703 *** 0.696 *** #> (0.002) (0.002) (0.002) (0.002) #> topic 0.999 *** 1.011 *** 1.000 *** #> (0.009) (0.009) (0.009) #> facebook -0.088 *** -0.089 *** #> (0.002) (0.002) #> gender 0.077 *** #> (0.002) #> ---------------------------------------------------------------------------------------------- #> AIC 692711.753 627181.581 612308.357 610880.109 609529.798 #> McFadden $R^2$ 0.486 0.534 0.545 0.546 0.547 #> ============================================================================================== #> *** p < 0.001; ** p < 0.01; * p < 0.05# }