Implements a Bayesian adaptive graphical lasso data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB routine proposed in Wang (2012) <doi:10.1214/12-BA729>.

Easy to use functions to visualize marker data
    from biparental populations. Useful for both analyzing and
    presenting genotypes in the ABH format.

Assess whether and how a specific continuous or categorical exposure affects the outcome of interest through one- or multi-dimensional mediators using an  adaptive bootstrap (AB) approach. The AB method allows to make inference for composite null hypotheses of no mediation effect, providing valid type I error control and thus optimizes statistical power. For more technical details, refer to He, Song and Xu (2024) <doi:10.1093/jrsssb/qkad129>.

Combine multidimensional arrays into a single array.
  This is a generalization of 'cbind' and 'rbind'.  Works with
  vectors, matrices, and higher-dimensional arrays (aka tensors).
  Also provides functions 'adrop', 'asub', and 'afill' for
  manipulating, extracting and replacing data in arrays.

The Brazilian Jurimetrics Association (ABJ in
    Portuguese, see <https://abj.org.br/> for more information) is
    a non-profit organization which aims to investigate and promote the
    use of statistics and probability in the study of Law and its
    institutions. This package has a set of datasets commonly used in
    our book.

The Brazilian Jurimetrics Association (ABJ in Portuguese, see
    <https://abj.org.br/> for more information) is a non-profit
    organization which aims to investigate and promote the use of
    statistics and probability in the study of Law and its institutions.
    This package implements general purpose tools used by ABJ, such as
    functions for sampling and basic manipulation of Brazilian lawsuits
    identification number. It also implements functions for text cleaning,
    such as accentuation removal.