An implementation of the iterative proportional fitting (IPFP), 
    maximum likelihood, minimum chi-square and weighted least squares procedures
    for updating a N-dimensional array with respect to given target marginal 
    distributions (which, in turn can be multidimensional). The package also
    provides an application of the IPFP to simulate multivariate Bernoulli
    distributions.

Generic functions to produce area/bar/box/line plots of data following IAMC (Integrated Assessment Modeling Consortium) submission format.

Lightweight parallel code execution and distributed computing.
    Designed for simplicity, a 'mirai' evaluates an R expression asynchronously,
    on local or network resources, resolving automatically upon completion.
    State of the art networking and concurrency via 'nanonext' and 'NNG'
    (Nanomsg Next Gen) offers reliable and efficient scheduling over fast
    inter-process communications or TCP/IP secured by TLS.

Allows 'mirai' objects encapsulating asynchronous computations,
    from the 'mirai' package by Gao (2023) <doi:10.5281/zenodo.7912722>, to be
    used interchangeably with 'promise' objects from the 'promises' package by
    Cheng (2021) <https://CRAN.R-project.org/package=promises>. This facilitates
    their use with packages 'plumber' by Schloerke and Allen (2022)
    <https://CRAN.R-project.org/package=plumber> and 'shiny' by Cheng, Allaire,
    Sievert, Schloerke, Xie, Allen, McPherson, Dipert and Borges (2022)
    <https://CRAN.R-project.org/package=shiny>.

Fitting recurrent events survival models for
    left-censored data with multiple imputation of the number of previous episodes.
    See Hernández-Herrera G, Moriña D, Navarro A. (2020) <arXiv:2007.15031>.

Estimates random effect latent measurement models, wherein the loadings, residual variances, intercepts, latent means, and latent variances all vary across groups. The random effect variances of the measurement parameters are then modeled using a hierarchical inclusion model, wherein the inclusion of the variances (i.e., whether it is effectively zero or non-zero) is informed by similar parameters (of the same type, or of the same item). This additional hierarchical structure allows the evidence in favor of partial invariance to accumulate more quickly, and yields more certain decisions about measurement invariance. Martin, Williams, and Rast (2020) <doi:10.31234/osf.io/qbdjt>.