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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.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.