Defines colour palettes and themes for Royal Statistical 
  Society (RSS) publications, including Significance magazine. Palettes and 
  themes are supported in both base R and 'ggplot2' graphics, and are intended 
  to be used by authors submitting to RSS publications.

Provides functions to access, search and download spacetime earth
    observation data via SpatioTemporal Asset Catalog (STAC). This package 
    supports the version 1.0.0 (and older) of the STAC specification
    (<https://github.com/radiantearth/stac-spec>). 
    For further details see Simoes et al. (2021) <doi:10.1109/IGARSS47720.2021.9553518>.

An extremely simple stack data type, implemented with 'R6'
    classes. The size of the stack increases as needed, and the amortized
    time complexity is O(1). The stack may contain arbitrary objects.

Provides fast, persistent (side-effect-free) stack, queue and
    deque (double-ended-queue) data structures. While deques include a superset
    of functionality provided by queues, in these implementations queues are
    more efficient in some specialized situations. See the documentation for
    rstack, rdeque, and rpqueue for details.

User-facing R functions are provided to parse, compile, test,
    estimate, and analyze Stan models by accessing the header-only Stan library
    provided by the 'StanHeaders' package. The Stan project develops a probabilistic
    programming language that implements full Bayesian statistical inference
    via Markov Chain Monte Carlo, rough Bayesian inference via 'variational'
    approximation, and (optionally penalized) maximum likelihood estimation via
    optimization. In all three cases, automatic differentiation is used to quickly
    and accurately evaluate gradients without burdening the user with the need to
    derive the partial derivatives.

Estimates previously compiled regression models using the 'rstan'
    package, which provides the R interface to the Stan C++ library for Bayesian
    estimation. Users specify models via the customary R syntax with a formula and
    data.frame plus some additional arguments for priors.