MonteCarloTest
MonteCarloTest refers to a statistical approach that uses Monte Carlo simulation to assess hypotheses. It estimates the sampling distribution of a test statistic under a null hypothesis by generating many random samples according to the null model and comparing the observed statistic to the simulated distribution.
In practice, the method involves: specifying a null hypothesis and a test statistic, generating a large number
MonteCarloTest encompasses several variants. It includes Monte Carlo randomization (permutation) tests, where data labels are shuffled
Implementation considerations include the need for a valid null model, an appropriate test statistic, and a
Applications span settings where analytical p-values are intractable, such as complex multivariate models, irregular data structures,