Fit Bayesian hierarchical models of animal abundance and occurrence
    via the 'rstan' package, the R interface to the 'Stan' C++ library.
    Supported models include single-season occupancy, dynamic occupancy, and
    N-mixture abundance models. Covariates on model parameters are specified
    using a formula-based interface similar to package 'unmarked', while also
    allowing for estimation of random slope and intercept terms. References:
    Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>;
    Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.

Basic statistical analyses. The package has been developed
    to be used in statistics courses at Bocconi University (Milan, Italy).
    Currently, the package includes some exploratory and inferential analyses
    usually presented in introductory statistics courses.

Calculates the Urban Centrality Index (UCI) as in Pereira et al., 
             (2013) <doi:10.1111/gean.12002>. The UCI measures the 
             extent to which the spatial organization of a city or region varies 
             from extreme polycentric to extreme monocentric in a continuous 
             scale from 0 to 1. Values closer to 0 indicate more polycentric patterns
             and values closer to 1 indicate a more monocentric urban form.

Returns a data frame with the names of the input data points and hex colors (or CIELab coordinates). Data can be mapped to colors for use in data visualization. It optimally maps data points into a polygon that represents the CIELab colour space. Since Euclidean distance approximates relative perceptual differences in CIELab color space, the result is a color encoding that aims to capture much of the structure of the original data.

Find and import datasets from the
    University of California Irvine Machine Learning (UCI ML) Repository into R.
    Supports working with data from UCI ML repository inside of R scripts, notebooks, 
    and 'Quarto'/'RMarkdown' documents. Access the UCI ML repository directly at
    <https://archive.ics.uci.edu/>.