Common utilities used in other MOSAIC-family packages are 
    collected here.

Data sets from Project MOSAIC (<http://www.mosaic-web.org>) used
    to teach mathematics, statistics, computation and modeling.  Funded by the
    NSF, Project MOSAIC is a community of educators working to tie together
    aspects of quantitative work that students in science, technology,
    engineering and mathematics will need in their professional lives, but
    which are usually taught in isolation, if at all.

Provides a framework for multipurpose optimal resource allocation in survey sampling,
    extending the classical optimal allocation principles introduced by Tschuprow (1923) and
    Neyman (1934) to multidomain and multivariate allocation problems. The primary method
    mosalloc() allows for the consideration of precision and cost constraints at the subpopulation
    level while minimizing either a vector of sampling errors or survey costs across a broad range
    of optimal sample allocation problems. The approach supports both single- and multistage
    designs. For single-stage stratified random sampling, the mosallocSTRS() function offers a user-
    friendly interface. Sensitivity analysis is supported through the problem's dual variables, which
    are naturally obtained via the internal use of the Embedded Conic Solver from the 'ECOSolveR'
    package. See Willems (2025, <doi:10.25353/ubtr-9200-484c-5c89>) for a detailed description
    of the theory behind 'MOSAlloc'.

Stability based methods for model order selection in clustering problems
 (Valentini, G (2007), <doi:10.1093/bioinformatics/btl600>).
 Using multiple perturbations of the data the stability of clustering solutions is assessed. Different
 perturbations may be used: resampling techniques, random projections and noise injection. Stability measures
 for the estimate of clustering solutions and statistical tests to assess their significance are provided.

Provides tools for analyzing Marshall-Olkin shock models semi-independent time.
    It includes interactive 'shiny' applications for exploring copula-based dependence 
    structures, along with functions for modeling and visualization. The methods are 
    based on Mijanovic and Popovic (2024, submitted) "An R package for Marshall-Olkin 
    shock models with semi-independent times."