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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