The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
group_regulation_long.matrix as the internal data format used by
TNA models for performance improvements across all functions.prepare_data() that resulted in
excessive console output.import_data() to read wide format
sequence data into long format.plot_frequencies() that can be used
to plot the state frequency distribution for both tna and
group_tna objects.permutation_test() is now a method for
both ungrouped (build_model()) and grouped
(group_model()) models. For grouped models, the function
performs the test between every unique pair of groups.adjust has been added for
permutation_test() to optionally adjust p-values using
p.adjust. By default, the p-values are not adjusted
(adjust = "none").groupwise has been added for
group_model(). When FALSE (the default),
scaling methods listed in scaling are performed globally
over the groups. When TRUE, the scaling is performed within
each group instead (this was the default behavior in previous versions
of the package).simulate() method for tna objects.
For models with type = "relative", this function simulates
sequence data based on the initial probabilities and transition
probability matrix.plot.tna_centralities() and
plot.group_tna_centralities() functions now plot the
centralities in the same order as provided in the measures
argument.plot.tna() and plot_model() functions
now use the median edge weight as the default value for the
cut argument.from and to columns in
bootstrap() output, which were inverted from the true edge
direction.bootstrap()
output, which plots the corresponding network where non-significant
edges have been pruned.permutation_test() function now properly checks
that its arguments x and y can be
compared.permutation_test() and
bootstrap() have been adjusted by adding 1 to both the
number of permutations/bootstrap samples and the number of extreme
events so that these estimates are never zero. The documentation has
also been clarified regarding p-values emphasizing that these are
estimates only.plot_compare() function now supports
negCol and posCol for specifying the color of
the positive and negative differences in transition and initial
probabilities.plot_mosaic() function now plots the x-axis on the
top and rotates the labels 90 degrees only when there are more than
three groups.detailed argument of
estimate_centrality_stability() has been removed.
Previously this argument had no effect on the output of the
function.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.
Health stats visible at Monitor.