Analytically calculates the operating characteristics of
    single-stage and two-stage basket trials with equal sample sizes using the
	power prior design by Baumann et al. (2024) <doi:10.48550/arXiv.2309.06988>
	and the design by Fujikawa et al. (2020) <doi:10.1002/bimj.201800404>.

Bayesian fitting and sensitivity analysis methods for adaptive
    spline surfaces described in <doi:10.18637/jss.v094.i08>. Built to handle continuous and categorical inputs as well as
    functional or scalar output. An extension of the methodology in Denison, Mallick
    and Smith (1998) <doi:10.1023/A:1008824606259>.

Estimates survival and mortality with covariates from census or capture-recapture/recovery data in a Bayesian framework when many individuals are of unknown age. It includes tools for data checking, model diagnostics and outputs such as life-tables and plots, as described in Colchero, Jones, and Rebke (2012) <doi:10.1111/j.2041-210X.2012.00186.x> and Colchero et al. (2021) <doi:10.1038/s41467-021-23894-3>.

Includes algorithms to assess alpha and beta diversity
    in all their dimensions (taxonomic, phylogenetic and functional).
    It allows performing a number of analyses based on species
    identities/abundances, phylogenetic/functional distances, trees,
    convex-hulls or kernel density n-dimensional hypervolumes
    depicting species relationships.
    Cardoso et al. (2015) <doi:10.1111/2041-210X.12310>.

Allows the user to manage easily R packages removal and installation. It offers many functions to display installed packages according to
    specific dates and removes them if needed. The user is always prompted when running the removal functions in order to confirm
    the required action. It also provides functions that will install 'Github' starred R packages whether available on 'CRAN' or not.

Functions to allow you to easily pass command-line arguments into R, and functions to aid in submitting your R code in parallel on a cluster and joining the results afterward (e.g. multiple parameter values for simulations running in parallel, splitting up a permutation test in parallel, etc.). See `parseCommandArgs(...)' for the main example of how to use this package.