Dataset contains select attributes for each match result since 1949-1950 season for UNC men's basketball team.

Implements Minimum Torsion for portfolio diversification as
    described in Meucci, Attilio (2013) <doi:10.2139/ssrn.2276632>.

Model data with a suspected clustering structure (either in 
    co-variate space, regression space or both) using a Bayesian product model 
    with a logistic regression likelihood. Observations are represented 
    graphically and clusters are formed through various edge removals or 
    additions. Cluster quality is assessed through the log Bayesian evidence of 
    the overall model, which is estimated using either a Sequential Monte Carlo 
    sampler or a suitable transformation of the Bayesian Information Criterion 
    as a fast approximation of the former. The internal Iterated Batch 
    Importance Sampling scheme (Chopin (2002 <doi:10.1093/biomet/89.3.539>)) is 
    made available as a free standing function.

Calculate several understandability metrics of BPMN models. BPMN stands for business process modelling notation and is a language for expressing business processes into business process diagrams. Examples of these understandability metrics are: average connector degree, maximum connector degree, sequentiality, cyclicity, diameter, depth, token split, control flow complexity, connector mismatch, connector heterogeneity, separability, structuredness and cross connectivity. See R documentation and paper on metric implementation included in this package for more information concerning the metrics.

A framework for estimating difference-in-differences with
 unpoolable data, based on Karim, Webb, Austin, and Strumpf (2024)
 <doi:10.48550/arXiv.2403.15910>. Supports common or staggered adoption, multiple
 groups, and the inclusion of covariates. Also computes p-values for the
 aggregate average treatment effect on the treated via the
 randomization inference procedure described in MacKinnon and Webb (2020)
 <doi:10.1016/j.jeconom.2020.04.024>.