Provides a suite of functions for analyzing sequences of events. Users can generate and code sequences based on predefined rules, with a special focus on the identification of sequences coded as 'ABA' (when one element appears, followed by a different one, and then followed by the first). Additionally, the package offers the ability to calculate the length of consecutive 'ABA'-coded sequences sharing common elements. The methods implemented in this package are based on the work by Ziembowicz, K., Rychwalska, A., & Nowak, A. (2022). <doi:10.1177/10464964221118674>.

Strings are abbreviated to at least "minlength" characters, such that they remain unique 
    (if they were). The abbreviations should be recognisable.

Implements several ABC algorithms for
        performing parameter estimation, model selection, and goodness-of-fit.
        Cross-validation tools are also available for measuring the
        accuracy of ABC estimates, and to calculate the
        misclassification probabilities of different models.

For a given data set, the package provides a novel method of computing precise limits to acquire subsets which are easily interpreted. Closely related to the Lorenz curve, the ABC curve visualizes the data by graphically representing the cumulative distribution function. Based on an ABC analysis the algorithm calculates, with the help of the ABC curve, the optimal limits by exploiting the mathematical properties pertaining to distribution of analyzed items. The data containing positive values is divided into three disjoint subsets A, B and C, with subset A comprising very profitable values, i.e. largest data values ("the important few"), subset B comprising values where the yield equals to the effort required to obtain it, and the subset C comprising of non-profitable values, i.e., the smallest data sets ("the trivial many"). Package is based on "Computed ABC Analysis for rational Selection of most informative Variables in multivariate Data", PLoS One. Ultsch. A., Lotsch J. (2015) <DOI:10.1371/journal.pone.0129767>.