Fits up to 20 nonlinear lactation curve models to dairy animal
    milk yield data. Models fitted include exponential, polynomial, mixed
    logarithmic, inverse polynomial, and sigmoid families published
    between 1923 and 2000. Supports batch processing of multiple animals
    from a single CSV file, with flexible selection of animals and models.
    Produces per-animal parameter tables, goodness-of-fit metrics including
    R-squared (R2), Root Mean Square Error (RMSE), Akaike Information
    Criterion (AIC), Bayesian Information Criterion (BIC), and a serial
    autocorrelation statistic, 15 diagnostic figures, and combined
    cross-animal comparison outputs.
    References: <doi:10.1085/jgp.5.4.441>, <doi:10.1038/216164a0>,
    <doi:10.1016/0301-6226(87)90003-0>, <doi:10.4141/cjas87-067>,
    <doi:10.3168/jds.S0022-0302(00)75136-8>.

Estimates lacunarity and generalized lacunarity for
    unidimensional binary time series. The lacunarity index summarizes the
    similarity of parts from different regions of a series at a given scale
    by averaging the behavior of variable size structures of zeros and ones.
    The generalized lacunarity concept provides an enhanced measure of the
    organization of the gaps over all measured scales and over the different
    arrangements of smaller and larger gaps in the series.

Functions for estimating the gliding box lacunarity (GBL),
    covariance, and pair-correlation of a random closed set (RACS) in 2D
    from a binary coverage map (e.g. presence-absence land cover maps).
    Contains a number of newly-developed covariance-based estimators of
    GBL (Hingee et al., 2019) <doi:10.1007/s13253-019-00351-9> and
    balanced estimators, proposed by Picka (2000)
    <http://www.jstor.org/stable/1428408>, for covariance, centred
    covariance, and pair-correlation.  Also contains methods for
    estimating contagion-like properties of RACS and simulating 2D Boolean
    models.  Binary coverage maps are usually represented as raster images
    with pixel values of TRUE, FALSE or NA, with NA representing
    unobserved pixels.  A demo for extracting such a binary map from a
    geospatial data format is provided.  Binary maps may also be
    represented using polygonal sets as the foreground, however for most
    computations such maps are converted into raster images.  The package
    is based on research conducted during the author's PhD studies.