A lightweight, dependency-free tool 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 and processes. 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>.

Unit testing for Monte Carlo methods, particularly Markov Chain Monte Carlo (MCMC) methods, are implemented as extensions of the 'testthat' package. The MCMC methods check whether the MCMC chain has the correct invariant distribution. They do not check other properties of successful samplers such as whether the chain can reach all points, i.e. whether is recurrent. The tests require the ability to sample from the prior and to run steps of the MCMC chain. The methodology is described in Gandy and Scott (2020) <arXiv:2001.06465>.

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>.

In the context of multistate models, which are popular in sociology,
    demography, and epidemiology, Markov chain with rewards calculations can
    help to refine transition timings and so obtain more accurate estimates. The
    package code accommodates up to nine transient states and irregular age (time)
    intervals. Traditional demographic life tables result as a special case.
    Formulas and methods involved are explained in detail in the accompanying
    article: Schneider / Myrskyla / van Raalte (2021): Flexible Transition Timing
    in Discrete-Time Multistate Life Tables Using Markov Chains with Rewards,
    MPIDR Working Paper WP-2021-002.