Bootstrap, permutation tests, and jackknife,
	featuring easy-to-use syntax.

Package of data sets from "Mathematical Statistics
    with Resampling in R" (1st Ed. 2011, 2nd Ed. 2018) by Laura Chihara and Tim Hesterberg.

Data sets for Chihara and Hesterberg (2022, ISBN: 978-1-119-87404-1)
    "Mathematical Statistics with Resampling in R" (3rd Ed).

Generate, simulate and visualise ODE models of consumer-resource 
    interactions. At its core, 'rescomp' provides a resource competition 
    modelling focused interface to 'deSolve', alongside flexible functions for 
    visualising model properties and dynamics. More information, documentation 
    and examples can be found on the package website.

Maximum likelihood estimation for univariate reducible
 stochastic differential equation models. Discrete, possibly noisy
 observations, not necessarily evenly spaced in time. Can fit
 multiple individuals/units with global and local parameters, by
 fixed-effects or mixed-effects methods. Ref.: Garcia, O. (2019)
 "Estimating reducible stochastic differential equations by
 conversion to a least-squares problem", Computational Statistics
 34(1): 23-46, <doi:10.1007/s00180-018-0837-4>.

Functions for dissimilarity analysis and machine learning in complex
    spectral data sets, including memory-based learning (MBL), optimal subset
    search and selection, and retrieval-based modelling with model libraries.
    Supports local learning, optimisation of spectral libraries, and
    ensemble prediction from precomputed models.
    Most of these functions are based on the methods presented in 
    Ramirez-Lopez et al. (2013) <doi:10.1016/j.geoderma.2012.12.014>.

Measure single-storage water supply system performance using resilience,
    reliability, and vulnerability metrics; assess storage-yield-reliability
    relationships; determine no-fail storage with sequent peak analysis; optimize
    release decisions for water supply, hydropower, and multi-objective reservoirs
    using deterministic and stochastic dynamic programming; generate inflow
    replicates using parametric and non-parametric models; evaluate inflow
    persistence using the Hurst coefficient.