Tools that facilitate ordinary differential equation (ODE) modeling in 'R'. This package allows one to perform simulations for ODE models that are encoded in the GNU 'MCSim' model specification language (Bois, 2009) <doi:10.1093/bioinformatics/btp162> using ODE solvers from the 'R' package 'deSolve' (Soetaert et al., 2010) <doi:10.18637/jss.v033.i09>.

Provides functionality to produce graphs of sampling distributions of test 	statistics from a variety of common statistical tests. With only a few keystrokes, 	the user can conduct a hypothesis test and visualize the test statistic and 		corresponding p-value through the shading of its sampling distribution. Initially       	created for statistics at Middlebury College.

A lightweight package designed to facilitate statistical 
    simulations through functional programming. It centralizes the simulation process into a single 
    higher-order function, enhancing manageability and usability without adding overhead from external 
    dependencies. The package includes ready-to-use functions for common simulation targets. A detailed example can be found on <https://github.com/ielbadisy/mcstatsim>.

Package computes popular and widely used multicollinearity diagnostic measures \doi{10.17576/jsm-2019-4809-26} and \doi{10.32614/RJ-2016-062}. Package also indicates which regressors may be the reason of collinearity among regressors.

A complete toolkit to process the Munich ChronoType 
    Questionnaire (MCTQ) for its three versions (standard, micro, and shift). 
    MCTQ is a quantitative and validated tool to assess chronotypes using 
    peoples' sleep behavior, originally presented by Till Roenneberg, Anna 
    Wirz-Justice, and Martha Merrow (2003, <doi:10.1177/0748730402239679>).

Application of a test to rule out that trends detected in hydrological time series are explained exclusively by the randomness of the climate. Based on: Ricchetti, (2018) <https://repositorio.uchile.cl/handle/2250/168487>.

Visualize the relationship between linear regression variables and causes of multi-collinearity. 
    Implements the method in Lin et. al. (2020) <doi:10.1080/10618600.2020.1779729>.