The developed function is designed to facilitate the seamless conversion of KML (Keyhole Markup Language)
             files to Shapefiles while preserving attribute values. It provides a straightforward interface for users
             to effortlessly import KML data, extract relevant attributes, and export them into the widely compatible
             Shapefile format. The package ensures accurate representation of spatial data while maintaining the integrity
             of associated attribute information. For details see, Flores, G. (2021). <DOI:10.1007/978-3-030-63665-4_15>.
             Whether for spatial analysis, visualization, or data interoperability, it simplifies the conversion process and 
             empowers users to seamlessly work with geospatial datasets.

An implementation of the 'k-means--' algorithm proposed
    by Chawla and Gionis, 2013 in their paper,
    "k-means-- : A unified approach to clustering and outlier detection.
    SIAM International Conference on Data Mining (SDM13)",
    <doi:10.1137/1.9781611972832.21>
    and using 'ordering' described by Howe, 2013 in the thesis,
    Clustering and anomaly detection in tropical cyclones".
    Useful for creating (potentially) tighter clusters than
    standard k-means and simultaneously finding outliers inexpensively
    in multidimensional space.

Datasets and functions for Klein and Moeschberger (1997),
        "Survival Analysis, Techniques for Censored and Truncated
        Data", Springer.

Produce Kaplan–Meier plots in the style recommended
    following the KMunicate study by Morris et al. (2019)
    <doi:10.1136/bmjopen-2019-030215>. The KMunicate style consists of
    Kaplan-Meier curves with confidence intervals to quantify uncertainty
    and an extended risk table (per treatment arm) depicting the number of
    study subjects at risk, events, and censored observations over time.
    The resulting plots are built using 'ggplot2' and can be further
    customised to a certain extent, including themes, fonts, and colour
    scales.