Implements multi-factor curve analysis for grouped data in 'R', replicating and
    extending the functionality of the the 'Stata' ado 'mfcurve' (Krähmer, 2023) <https://ideas.repec.org/c/boc/bocode/s459224.html>. 
	Related to the idea of specification curve analysis (Simonsohn, Simmons, and Nelson, 2020) <doi:10.1038/s41562-020-0912-z>.
	Includes data preprocessing, statistical testing, and visualization of results with confidence intervals.

Computing functional traits-based distances between pairs of 
    species for species gathered in assemblages allowing to build several
    functional spaces. The package allows to compute functional diversity
    indices assessing the distribution of species (and of their dominance) in a
    given functional space for each assemblage and the overlap between
    assemblages in a given functional space, see: Chao et al. (2018)
    <doi:10.1002/ecm.1343>, Maire et al. (2015) <doi:10.1111/geb.12299>,
    Mouillot et al. (2013) <doi:10.1016/j.tree.2012.10.004>, Mouillot et al.
    (2014) <doi:10.1073/pnas.1317625111>, Ricotta and Szeidl (2009)
    <doi:10.1016/j.tpb.2009.10.001>. Graphical outputs are included.
    Visit the 'mFD' website for more information, documentation and examples.

Creates and manages a PostgreSQL database suitable for storing fisheries data
             and aggregating ready for use within a Gadget <https://gadget-framework.github.io/gadget2/> model.
             See <https://mareframe.github.io/mfdb/> for more information.

Contains the MultiFractal Detrended Fluctuation Analysis (MFDFA), 
  MultiFractal Detrended Cross-Correlation Analysis (MFXDFA), and the Multiscale
  Multifractal Analysis (MMA). The MFDFA() function proposed in this package was 
  used in Laib et al. (<doi:10.1016/j.chaos.2018.02.024> and <doi:10.1063/1.5022737>). 
  See references for more information. Interested users can find a parallel version of
  the MFDFA() function on GitHub.

Methods for controlling the median of the false discovery proportion (mFDP).
	Depending on the method, simultaneous or non-simultaneous inference is provided. 
	The methods take a vector of p-values or test statistics as input.