**Fast K-Mer Counting and Clustering for Biological Sequence Analysis** (**kmer**)

Contains tools for rapidly computing distance matrices and clustering large sequence datasets using fast alignment-free k-mer counting and recursive k-means partitioning. See Vinga and Almeida (2003) <doi:10.1093/bioinformatics/btg005> for a review of k-mer counting methods and applications for biological sequence analysis.

**Analysis of Scientific Evidence Using Bayesian and Likelihood Methods** (**evidence**)

Bayesian (and some likelihoodist) functions as alternatives to hypothesis-testing functions in R base using a user interface patterned after those of R’s hypothesis testing functions. See McElreath (2016, ISBN: 978-1-4822-5344-3), Gelman and Hill (2007, ISBN: 0-521-68689-X) (new edition in preparation) and Albert (2009, ISBN: 978-0-387-71384-7) for good introductions to Bayesian analysis and Pawitan (2002, ISBN: 0-19-850765-8) for the Likelihood approach. The functions in the package also make extensive use of graphical displays for data exploration and model comparison.

**Simulations and Statistical Inference for Linear Fractional Stable Motions** (**rlfsm**)

Contains functions for simulating linear fractional stable motions, according to techniques developed by Stoev and Taqqu (2004) <doi:10.1142/S0218348X04002379>, as well as functions for computing important statistics used with these processes introduced by Mazur, Otryakhin and Podolskij (2018) <arXiv:1802.06373>, and also different quantities related to those statistics.

**ChIP-Seq Processing Pipeline** (**spp**)

Description: R package for analysis of ChIP-seq and other functional sequencing data.

**Calculator of Understandability Metrics for BPMN** (**understandBPMN**)

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.

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