Performs angle-based outlier detection on a given dataframe. Three methods are available, a full but slow implementation using all the data that has cubic complexity, a fully randomized one which is way more efficient and another using k-nearest neighbours. These algorithms are specially well suited for high dimensional data outlier detection.

An implementation of the Abnormal Blood Profile Score (ABPS,
    part of the Athlete Biological Passport program of the World Anti-Doping
    Agency), which combines several blood parameters into a single score in
    order to detect blood doping (Sottas et al. (2006)
    <doi:10.2202/1557-4679.1011>). The package also contains functions to
    calculate other scores used in anti-doping programs, such as the
    OFF-score (Gore et al. (2003) <http://www.haematologica.org/content/88/3/333>),
    as well as example data.

This toolkit implements a numerical solution algorithm 
    to invert a quality of life measure from observed data. Unlike
    the traditional Rosen-Roback measure, this measure accounts for
    mobility frictions—generated by idiosyncratic tastes and local
    ties — and trade frictions — generated by trade costs and
    non-tradable services, thereby reducing non-classical
    measurement error. The QoL measure is based on Ahlfeldt, Bald,
    Roth, Seidel (2024)
    <https://econpapers.repec.org/RePEc:boc:bocode:s459382>
    "Measuring Quality of Life under Spatial Frictions". When using
    this programme or the toolkit in your work, please cite the paper.

Wraps the 'Abseil' 'C++' library for use by R packages.
    Original files are from <https://github.com/abseil/abseil-cpp>.
    Patches are located at
    <https://github.com/doccstat/abseil-r/tree/main/local/patches>.

A variable selection method using B-Splines in multivariate nOnparametric Regression models Based on partial dErivatives Regularization (ABSORBER) implements a novel variable selection method in a nonlinear multivariate model using B-splines. For further details we refer the reader to the paper Savino, M. E. and Lévy-Leduc, C. (2024), <https://hal.science/hal-04434820>.