Given a multivariate dataset and some knowledge about the dependencies 
              between its features, it is customary to fit a statistical model to the features 
              to infer parameters of interest. Such a procedure implicitly assumes that the 
              sample is exchangeable. This package provides a flexible non-parametric test 
              of this exchangeability assumption, allowing the user to specify the feature 
              dependencies by hand as long as features can be grouped into disjoint independent sets. 
              This package also allows users to test a dual hypothesis, which is, given that the 
              sample is exchangeable, does a proposed grouping of the features into disjoint sets
              also produce statistically independent sets of features? See Aw, Spence and Song (2023) 
              for the accompanying paper.

It implements many univariate and multivariate permutation (and
    rotation) tests. Allowed tests: the t one and two samples, ANOVA, linear
    models, Chi Squared test, rank tests (i.e. Wilcoxon, Mann-Whitney,
    Kruskal-Wallis), Sign test and Mc Nemar. Test on Linear Models are
    performed also in presence of covariates (i.e. nuisance parameters).
    The permutation and the rotation methods to get the null distribution of
    the test statistics are available. It also implements methods for
    multiplicity control such as Westfall & Young minP procedure and Closed
    Testing (Marcus, 1976) and k-FWER. Moreover, it allows to test for fixed
    effects in mixed effects models.

Flipbooks present code step-by-step and side-by-side with its output.  'flipbookr' helps creators build flipbooks efficiently because code pipelines are automatically parsed and prepped for presentation as flipbooks.

Allows the user to create a countdown in 'RMarkdown' documents and 'shiny' applications. 
    The package is a wrapper of the 'JavaScript' library 'flipdown.js'. See <https://pbutcher.uk/flipdown/> for more info.