Nothing
lifecycle::badge() in Roxygen docs because of
CRAN Note..data$ to simply "" in all functions to fix test
warnings from dplyr.rhub GitHub Action workflow to check CRAN compatibility
more fully.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 effectsnc_estimate_*_links() functions to set
thresholds for classifying links (#157)as_edge_tbl() (#142)nc_classify_effects() and nc_filter_estimates(), merged
them into the two main estimation functions insteadlm and glm models were removed for
improving computing speed (they slowed things down quite a bit)nc_estimate_* functions output@seealsolm and glm models, model summary statistics are added (#88).nc_plot_network() (#89, #110).nc_adjacency_graph(),
nc_adjacency_matrix(), and nc_partial_corr_matrix() to help
create the weights for the network plot. (Issue #80, PR #89).pcor() (#125,
#131).nc_filter_estimates() (#109).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).matches() or starts_with()
(#73).net_coupler_out(), getExp.coef.permetabolite(), and
getExp.coef.out() (#59)nc_exposure_estimates()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().nc_create_network() and the outcome
estimation functions. Travis and code coverage were added as well.nc_make_network() to nc_create_network() and moved into
own file.nc_make_network() code and moved into another file.NEWS.md file to track changes to the package.Any scripts or data that you put into this service are public.
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