tna 0.5.0
- Added a new dataset
group_regulation_long.
tna 0.4.9
- Switched to
matrix as the internal data format used by
TNA models for performance improvements across all functions.
tna 0.4.8
- Fixed an issue with
prepare_data() that resulted in
excessive console output.
tna 0.4.7
- Added the function
import_data() to read wide format
sequence data into long format.
tna 0.4.6
- Added the function
plot_frequencies() that can be used
to plot the state frequency distribution for both tna and
group_tna objects.
tna 0.4.5
- The function
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.
- A new argument
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").
- A new argument
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).
- Added a
simulate() method for tna objects.
For models with type = "relative", this function simulates
sequence data based on the initial probabilities and transition
probability matrix.
tna 0.4.4
- The
plot.tna_centralities() and
plot.group_tna_centralities() functions now plot the
centralities in the same order as provided in the measures
argument.
- The
plot.tna() and plot_model() functions
now use the median edge weight as the default value for the
cut argument.
- Fixed the
from and to columns in
bootstrap() output, which were inverted from the true edge
direction.
- A plot method has been added for the
bootstrap()
output, which plots the corresponding network where non-significant
edges have been pruned.
tna 0.4.3
- The
permutation_test() function now properly checks
that its arguments x and y can be
compared.
- The p-value calculations of
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.
tna 0.4.2
- The
plot_compare() function now supports
negCol and posCol for specifying the color of
the positive and negative differences in transition and initial
probabilities.
- The
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.
tna 0.4.1
- The
detailed argument of
estimate_centrality_stability() has been removed.
Previously this argument had no effect on the output of the
function.
- Removed several duplicated entries in the documentation.
tna 0.4.0
- The
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.
- The
prepare_data() function now supports
order when used together with time and
actor.
- The
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.
- Added the function
compare() to compare
tna models and weight matrices. This function produces an
object of class tna_comparison which has
print() and plot() methods.
- Added the function
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.
- Fixed an issue with
plot.tna_communities() which now
checks for the availability of a particular community detection method
before plotting.
- Made several arguments in the plot methods of the package accessible
to the user.
tna 0.3.2
event2sequence() has been renamed to
prepare_data(). The function is now also more general and
can process more date formats.- Added a
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".
- Fixed an issue with
permutatation_test() when
x and y had a differing number of
columns.
- Community detection methods can now be selected using the
methods argument in communities().
- The
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.
- Removed all
verbose arguments in favor of
options(rlib_message_verbosity = "quiet"). and
options(rlib_warning_verbosity = "quiet").
tna 0.3.1
- Fixed an issue when checking the validity of
character
type arguments.
- Improved the
bootstrap() function to determine edge
significance based on deviation from the observed value, rather than a
fixed threshold.
- Added a helper function
event2sequence() to parse event
data into sequence data.
tna 0.3.0
- Added support for grouped sequence data (clusters).
tna 0.2.0
- Added bootstrapping, permutation test, and centrality stability
functionalities.
tna 0.1.0