NEWS

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.

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.

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.

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.

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.

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.

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.

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").

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.

Added bootstrapping, permutation test, and centrality stability functionalities.