Facilitate the evaluation of forecasts in a convenient
    framework based on data.table. It allows user to to check their forecasts
    and diagnose issues, to visualise forecasts and missing data, to transform
    data before scoring, to handle missing forecasts, to aggregate scores, and
    to visualise the results of the evaluation. The package mostly focuses on
    the evaluation of probabilistic forecasts and allows evaluating several
    different forecast types and input formats. Find more information about the
    package in the Vignettes as well as in the accompanying paper,
    <doi:10.48550/arXiv.2205.07090>.

A consistent, semi-supervised, non-parametric survival curve estimator optimized for efficient use of Electronic Health Record (EHR) data with a limited number of current status labels. See van der Laan and Robins (1997) <doi:10.2307/2670119>.

Constructs gene regulatory networks from single-cell gene expression data using the PANDA (Passing Attributes between Networks for Data Assimilation) algorithm.

An accurate and easy tool for performing linear trajectory inference on
  single cells using single-cell RNA sequencing data. In addition, 'SCORPIUS'
  provides functions for discovering the most important genes with respect to
  the reconstructed trajectory, as well as nice visualisation tools.
  Cannoodt et al. (2016) <doi:10.1101/079509>.

Perform the balanced (Scott and Knott, 1974) and unbalanced <doi:10.1590/1984-70332017v17n1a1> Scott & Knott algorithm.

The Scott-Knott Effect Size Difference (ESD) test is a mean comparison approach that leverages a hierarchical clustering to partition the set of treatment means (e.g., means of variable importance scores, means of model performance) into statistically distinct groups with non-negligible difference [Tantithamthavorn et al., (2018) <doi:10.1109/TSE.2018.2794977>].

Implements the Scout method for regression, described in "Covariance-regularized regression and classification for high-dimensional problems", by Witten and Tibshirani (2008),  Journal of the Royal Statistical Society, Series B 71(3): 615-636.