Plotting toolbox for 2D oceanographic data (satellite data, sea surface temperature, chlorophyll, ocean fronts & bathymetry). Recognized classes and formats include netcdf, Raster, '.nc' and '.gz' files.

Functions for transforming and viewing 2-D and 3-D (oceanographic) data and model output.

Calculate ocean wave height summary statistics and process data 
    from bottom-mounted pressure sensor data loggers. Derived primarily from 
    MATLAB functions provided by U. Neumeier at 
    <http://neumeier.perso.ch/matlab/waves.html>. Wave number 
    calculation based on the algorithm in Hunt, J. N. (1979, ISSN:0148-9895) 
    "Direct Solution of Wave Dispersion Equation", American Society of Civil 
    Engineers Journal of the Waterway, Port, Coastal, and Ocean Division, 
    Vol 105, pp 457-459.

Estimates win ratio or Mann-Whitney parameter for two group
 comparisons using ordered composite endpoints with right censoring
 as described in Follmann, Fay, Hamasaki, and Evans (2020)<doi:10.1002/sim.7890>.

Several Oceanographic data sets are provided for use
    by the 'oce' package and for other purposes.

Nonparametric estimator for ordered non-numeric outcomes. The estimator modifies a
    standard random forest splitting criterion to build a collection of forests, each estimating the conditional 
    probability of a single class. The package also implements a nonparametric estimator of the covariates’ marginal effects.

Extends 'flexclust' with an R implementation of order constrained
  solutions in k-means clustering (Steinley and Hubert, 2008, <doi:10.1007/s11336-008-9058-z>).

Provides a function to detect and trim outliers in Gaussian mixture model-based clustering using methods described in Clark and McNicholas (2022) <arXiv:1907.01136>.

Generate and analyze Optimal Channel Networks (OCNs): 
	oriented spanning trees reproducing all scaling features characteristic 
	of real, natural river networks. As such, they can be used in a variety 
	of numerical experiments in the fields of hydrology, ecology and 
	epidemiology. See Carraro et al. (2020) <doi:10.1002/ece3.6479> 
	for a presentation of the package; Rinaldo et al. (2014) 
	<doi:10.1073/pnas.1322700111> for a theoretical overview on the OCN 
	concept; Furrer and Sain (2010) <doi:10.18637/jss.v036.i10> for the 
	construct used.