The encoding of colour can be handled in many different ways,
    using different colour spaces. As different colour spaces have
    different uses, efficient conversion between these representations are
    important. The 'farver' package provides a set of functions that gives
    access to very fast colour space conversion and comparisons
    implemented in C++, and offers speed improvements over the
    'convertColor' function in the 'grDevices' package.

The 'FAS' package implements the bootstrap method for the tuning parameter selection and tuning-free inference on sparse regression coefficient vectors. Currently, the test could be applied to linear and factor-augmented sparse regressions, see Lederer & Vogt (2021, JMLR) <https://www.jmlr.org/papers/volume22/20-539/20-539.pdf> and Beyhum & Striaukas (2023) <arXiv:2307.13364>.

An implementation of the two-sample multivariate
    Kolmogorov-Smirnov test described by Fasano and Franceschini (1987)
    <doi:10.1093/mnras/225.1.155>. This test evaluates the null hypothesis
    that two i.i.d. random samples were drawn from the same underlying
    probability distribution. The data can be of any dimension, and can be
    of any type (continuous, discrete, or mixed).

Latent process embedding for functional network data with the Functional Adjacency Spectral Embedding. Fits smooth latent processes based on cubic spline bases. Also generates functional network data from three models, and evaluates a network generalized cross-validation criterion for dimension selection. For more information, see MacDonald, Zhu and Levina (2022+) <arXiv:2210.07491>.

A collection of functions to manage, to investigate and to analyze data sets of financial 
  assets from different points of view.

Implementation of the FASSTER (Forecasting with Additive Switching 
    of Seasonality, Trend, and Exogenous Regressors) model for forecasting time 
    series with multiple seasonal patterns. The model combines state space 
    methodology with a switching component in the observation equation to allow 
    flexible modeling of complex seasonal patterns, including time-varying 
    effects and multiple seasonalities.