nc_estimate_*function output the full model list as an attribute, that is really only necessary for those interested in the underlying models used for classifying the effects
nc_estimate_*_links()functions to set thresholds for classifying links (#157)
nc_filter_estimates(), merged them into the two main estimation functions instead
glmmodels were removed for improving computing speed (they slowed things down quite a bit)
glmmodels, model summary statistics are added (#88).
nc_partial_corr_matrix()to help create the weights for the network plot. (Issue #80, PR #89).
nc_standardize()that prevented the ability to use the
.regressed_on. argument to extract residuals (#108).
nc_standardize()function to standardize the metabolic variables (#73).
nc_outcome_estimates()function. Because of this streamlining, the code is much faster and with the move to use MuMIn we can remove our dependency on rJava via glmulti.
nc_create_network()function so that only the graph skeleton is output (#55).
nc_create_network()and the outcome estimation functions. Travis and code coverage were added as well.
nc_create_network()and moved into own file.
nc_make_network()code and moved into another file.