Constructs a space-filling design under the criterion of maximum-minimum distance. Both discrete and continuous searches are provided.

Implementation of the sampling and aggregation method for the covariate shift maximin effect, which was proposed in <doi:10.48550/arXiv.2011.07568>. It constructs the confidence interval for any linear combination of the high-dimensional maximin effect.

Performs maximal interaction two-mode clustering, permutation tests, scree plots, and interaction 
    visualizations for bicluster analysis. See
    Ahmed et al. (2025) <doi:10.17605/OSF.IO/AWGXB>, Ahmed et al. (2023) <doi:10.1007/s00357-023-09434-2>,
    Ahmed et al. (2021) <doi:10.1007/s11634-021-00441-y>.

Functions for Maximum Likelihood (ML) estimation, non-linear
   optimization, and related tools.  It includes a unified way to call
   different optimizers, and classes and methods to handle the results from
   the Maximum Likelihood viewpoint.  It also includes a number of convenience
   tools for testing and developing your own models.

Provides a likelihood-based approach to modeling species distributions using presence-only data. In contrast to the popular software program MAXENT, this approach yields estimates of the probability of occurrence, which is a natural descriptor of a species' distribution.

Computes the maximum matching for unweighted graph and maximum
    matching for (un)weighted bipartite graph efficiently.

An implementation of the Monte Carlo techniques described in details by Dufour (2006) <doi:10.1016/j.jeconom.2005.06.007> and Dufour and Khalaf (2007) <doi:10.1002/9780470996249.ch24>. The two main features available are the Monte Carlo method with tie-breaker, mc(), for discrete statistics, and the Maximized Monte Carlo, mmc(), for statistics with nuisance parameters.

Procedures to fit species distributions models from occurrence records and environmental variables, using 'glmnet' for model fitting. Model structure is the same as for the 'Maxent' Java package, version 3.4.0, with the same feature types and regularization options.  See the 'Maxent' website <http://biodiversityinformatics.amnh.org/open_source/maxent> for more details.