Provides a forecasting method that maps vast numbers of
    (scalar-valued) signals of any type into an aggregate density forecast
    in a time-varying and computationally fast manner. The method proceeds
    in two steps: First, it transforms a predictive signal into a density
    forecast. Second, it combines the generated candidate density
    forecasts into an ultimate density forecast. The methods are explained
    in detail in Adaemmer et al. (2023) <doi:10.2139/ssrn.4342487>.

Provides an interface to 'HDFql' <https://www.hdfql.com/> 
    and helper functions for reading data from and writing data to 'HDF5' files. 'HDFql' 
    provides a high-level language for managing 'HDF5' data that is platform independent.
    For more information, see the reference manual 
    <https://www.hdfql.com/resources/HDFqlReferenceManual.pdf>.

Test the significance of coefficients in high dimensional generalized linear models.

Implementation of multiple approaches to perform inference in high-dimensional models.

A correlation-based batch process for fast, accurate imputation for 
    high dimensional missing data problems via chained random forests.
    See Waggoner (2023) <doi:10.1007/s00180-023-01325-9> for more on 'hdImpute',
    Stekhoven and Bühlmann (2012) <doi:10.1093/bioinformatics/btr597> for more on 'missForest', 
    and Mayer (2022) <https://github.com/mayer79/missRanger> for more on 'missRanger'.

A generic function and a set of methods to calculate highest density intervals for a variety of classes of objects which can specify a probability density distribution, including MCMC output, fitted density objects, and functions.

We provide an R tool for computation and nonparametric plug-in estimation of Highest Density Regions (HDRs) and general level sets in the directional setting. Concretely, circular and spherical HDRs can be reconstructed from a data sample following Saavedra-Nieves and Crujeiras (2021) <doi:10.1007/s11634-021-00457-4>. This library also contains two real datasets in the circular and spherical settings. The first one concerns a problem from animal orientation studies and the second one is related to earthquakes occurrences.