Provides tools to process raster data and apply Otsu-based thresholding for burned area mapping and other image segmentation tasks. Implements the method described by Otsu (1979) <doi:10.1109/TSMC.1979.4310076>, a data-driven technique that determines an optimal threshold by maximizing the inter-class variance of pixel intensities. It includes validation functions to assess segmentation accuracy against reference data using standard accuracy metrics such as precision, recall, and F1-score.

An optimal transport (OT) method, which can handle tensors of any order by learning possibly multiple transport plans. For the details of the methods, see Kerdoncuff et al. (2022) <doi:10.1609/aaai.v36i7.20695>.

An R autograding extension for Otter-Grader (<https://otter-grader.readthedocs.io>). It supports 
    grading R scripts, R Markdown documents, and R Jupyter Notebooks.

Tools for converting Open-Source Tools for Training Resources
    (OTTR) courses into Leanpub or Coursera courses. 'ottrpal' is for use
    with the OTTR Template repository to create courses.

Summarizes the taxonomic composition, diversity contribution of the rare and abundant community by using OTU (operational taxonomic unit) table which was generated by analyzing pipeline of 'QIIME' or 'mothur'. The rare biosphere in this package is subset by the relative abundance threshold (for details about rare biosphere please see Lynch and Neufeld (2015) <doi:10.1038/nrmicro3400>).

Analyses of OTU tables produced by 16S rRNA gene amplicon sequencing, as well as example data. It contains the data and scripts used in the paper Linz, et al. (2017) "Bacterial community composition and dynamics spanning five years in freshwater bog lakes," <doi: 10.1128/mSphere.00169-17>.

Fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.

The Open University Learning Analytics Dataset (OULAD) is available from 
    Kuzilek et al. (2017) <doi:10.1038/sdata.2017.171>.  The 'ouladFormat' 
    package loads, cleans and formats the OULAD for data analysis (each row of the
    returned data set is an individual student). The package’s main function,
    combined_dataset(), allows the user to choose whether the returned
    data set includes assessment, demographics, virtual learning environment (VLE),
    or registration variables etc.