Software to support the introductory *MOSAIC Calculus* 
    textbook <https://www.mosaic-web.org/MOSAIC-Calculus/>),
    one of many data- and modeling-oriented educational resources developed by 
    Project MOSAIC (<https://www.mosaic-web.org/>). Provides symbolic and
    numerical differentiation and integration, as well as support for 
    applied linear algebra (for data science), and differential equations/dynamics.
    Includes grammar-of-graphics-based functions for drawing vector fields, trajectories, etc.
    The software is suitable for general use, but intended mainly for teaching calculus.

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.

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."

This project aims to make an accessible model for mosquito control resource optimization. The model uses data provided by users to estimate the mosquito populations in the sampling area for the sampling time period, and the optimal time to apply a treatment or multiple treatments.