removed dependency from extraDistr (orphaned
package):
introduced helper functions for handling multivariate
hypergeometric density and sampling: dmvhyper_base and
rmvhyper_base.
fixed reversed dependency issues for dplyr:::id “no visible binding for global variable ‘id’” errors.
bug fixes:
bccm(): fixed bug that returned wrongly filled
omegaBlock matrix. The bug did not affect the model fit itself.
new features:
extended testing scripts of package
bug fixes:
logl() and rghype(): fixed bug that
treated as a hypergeometric model a ghype where all odds are equal to 0.
Throws error instead.
compute_xi(): Fixed a bug that introduced spurious
stubs for nodes with zero degrees when creating a Xi matrix without
selfloops
link_significance(): fixed bug when under=TRUE,
updated implementation to improve performance
ghype(): fixed computation of degrees of freedom for
full model where xi has zero values
link_significance(): When calling with under = FALSE
and pval = FALSE was returning phi(0) = 1 instead of Pr(x>0)function renaming:
linkSignificance() –>
link_significance()
ComputeXi() –> compute_xi()
new features
updated documentation for endogenous statistics functions
introduced a new function get_zero_dummy() that
generates the dummy variable to be used together with endogenous
statistics functions.
added testing with test_that
check_specs(): recognize bipartite graphs
addressed issue #15: bccm now names coefficients according to label names. E.g.: coefficient for the propensities between block ‘red’ and ‘blue’ are now named ‘red<->blue’.
bug fixes:
scm(): fixed df for bipartite graphs
linkSignificance(): fixed issue for bipartite
graphs
bccm(): fixed issue when fitting to bipartite
graphs
bccm(): fixed issue arising when passing a list of
identical labels (all vertices in one block)
NEWS.md file to track changes to the
package.check_specs() that threw an error when
the function was called without additional parameters.bccm() to improve its speed when passing a
large number of labels.nrmSelection(), createPredictors,
and nrmChoose() to nrm_selection(),
create_predictors, and nrm_choose()
respectively, to standardise functions’ names.nrm_selection() and nrm_choose()
to use ‘pbmclapply’ and show a progress bar.