A data mining approach for longitudinal and clustered data, 
        which combines the structure of mixed effects model with tree-based 
        estimation methods. See Sela, R.J. and Simonoff, J.S. (2012) RE-EM 
        trees: a data mining approach for longitudinal and clustered data 
        <doi:10.1007/s10994-011-5258-3>.

Implements an objective Bayes intrinsic conditional autoregressive 
    prior. This model provides an objective Bayesian approach for modeling spatially 
    correlated areal data using an intrinsic conditional autoregressive prior on a vector of 
    spatial random effects.

A robust alternative to the traditional principal component estimator is proposed within the framework of factor models, known as Robust Exponential Factor Analysis, specifically designed for the modeling of high-dimensional datasets with heavy-tailed distributions. The algorithm estimates the latent factors and the loading by minimizing the exponential squared loss function. To determine the appropriate number of factors, we propose a modified rank minimization technique, which has been shown to significantly enhance finite-sample performance.

Reference database manager offering a set of functions
    to import, organize, clean, filter, audit and export reference genetic
    data. Provide functions to download sequence data from
    Bold Systems (<https://www.boldsystems.org/>) and
    NCBI GenBank <https://www.ncbi.nlm.nih.gov/genbank/>.
    Designed as an environment for semi-automatic and assisted
    construction of reference databases and to improve standardization
    and repeatability in barcoding and metabarcoding studies.

Allows users to easily create references to R objects then
    'dereference' when needed or modify in place without using reference 
    classes, environments, or active bindings as workarounds. Users can 
    also create expression references that allow subsets of any object to 
    be referenced or expressions containing references to multiple 
    objects.