Triangular and trapezoidal fuzzy numbers are used to study fuzzy logic,
    fuzzy reasoning and approximating, fuzzy regression models, etc.
    This package builds the generating function for triangular and trapezoidal fuzzy numbers based on Souliotis et al. (2022)<doi:10.3390/math10183350>. 
    They proposed a method for the construction of fuzzy numbers via a cumulative distribution function based on the possibility theory.

Inference, goodness-of-fit tests, and predictions for continuous and discrete univariate  Hidden Markov Models (HMM), including zero-inflated distributions. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the p-value. The description of the methodology is taken from Nasri et al (2020) <doi:10.1029/2019WR025122>.

Implements a basic version of the hierarchical clustering algorithm
    'Genie' which links two point groups in such a way that
    an inequity measure (namely, the Gini index) of the cluster sizes
    does not significantly increase above a given threshold.
    This method most often outperforms many other data segmentation approaches
    in terms of clustering quality as tested on a wide range of benchmark
    datasets. At the same time, Genie retains the high speed of the single
    linkage approach, therefore it is also suitable for analysing larger data sets.
    For more details see (Gagolewski et al. 2016 <DOI:10.1016/j.ins.2016.05.003>).
    For a faster and more feature-rich implementation, see the 'genieclust' package
    (Gagolewski, 2021 <DOI:10.1016/j.softx.2021.100722>).

The American Association Research (AACR) Project
    Genomics Evidence Neoplasia Information Exchange (GENIE) BioPharma
    Collaborative represents a multi-year, multi-institution effort
    to build a pan-cancer repository of linked clinico-genomic data.
    The genomic and clinical data are provided in multiple releases (separate
    releases for each cancer cohort with updates following data corrections),
    which are stored on the data sharing platform
    'Synapse' <https://www.synapse.org/>.
    The 'genieBPC' package provides a seamless way to obtain the
    data corresponding to each release from 'Synapse' and to prepare
    datasets for analysis.