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prepare_data() function now produces an object of
class tna_data, which can be directly used as an argument
to build_model() and other methods.prepare_data() function now supports
order when used together with time and
actor.prepare_data() function gains the
unused_fn argument of tidyr::pivot_wider() to
process any extra columns. The default is to keep all columns and use
the first value.compare() to compare
tna models and weight matrices. This function produces an
object of class tna_comparison which has
print() and plot() methods.plot_mosaic() which can be used to
produce mosaic plots of transition counts for frequency-based transition
network models and to contrast the state counts between groups.plot.tna_communities() which now
checks for the availability of a particular community detection method
before plotting.event2sequence() has been renamed to
prepare_data(). The function is now also more general and
can process more date formats.method argument to bootstrap().
The new default option "stability" implements a
bootstrapping scheme where the edge weights are compared against a range
of “consistent” weights (see the documentation for details). The old
functionality can be accessed with
method = "threshold".permutatation_test() when
x and y had a differing number of
columns.methods argument in communities().build_model() function has gained the argument
cols which can be used to subset the columns of the data
for stslist and data.frame inputs.verbose arguments in favor of
options(rlib_message_verbosity = "quiet"). and
options(rlib_warning_verbosity = "quiet").character
type arguments.bootstrap() function to determine edge
significance based on deviation from the observed value, rather than a
fixed threshold.event2sequence() to parse event
data into sequence data.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.