NEWS.md
norm_logmeans() has a raised cap before triggering a warning message.find_outliers() now as the verbose argument which, by default, suppresses the warning message triggered when there is not enough data.code_allophones() now added.norm_logmeans() now added, which does a log-means normalization based on Barreda & Nearey (2018).norm_anae() updated. The use_telser_g argument has been changed to simply g. Previously, if you wnated to calculate g internally, you’d do use_telsur_g = FALSE and that code didn’t work. Now, you’d say g = "calculate", and that does work this time. Additionally, some new functionality is that g can be set to any arbitrary value, such as zero: g = 0.arpa_to_keywords() has been replaced with the more robust and flexible switch_transcriptions.manova_p() now added.norm_anae() now uses the Telsur G by default. This can be suppressed and a new G value can be calculated using the data (the old default behavior), by specifying use_telsur_g = FALSE.norm_anae() now requires the data to be grouped by speaker prior to running. This makes it more consistent with the other normalization procedures in this package.wells_to_arpa() was created, as an inverse function to arpa_to_wells() because I needed it one time.norm_deltaF() has been fixed so that including F4 now works. Additional arguments have been added as well.pillai() and tidy_mahalanobis() get much clearer examples and much more documentation.arpa_to_keywords() no longer crashes if a dataset didn’t have all vowels present.arpa_to_keywords() and arpa_to_wells() added.joeysvowels package, a remote dependency.norm_anae() is now more robust (thanks, Thomas!)hz, bark, spread_n, move_x_before_y, move_x_after_y, and all the functions related to the old outlier detection procedure (joey_filter, joey_do_pca, joey_adjust_cutoff, joey_rm_outliers).NEWS.md file to track changes to the package.