Performs calculations with tree taper (or stem
    profile) equations, including model fitting. The package
    implements the methods from García, O. (2015) "Dynamic
    modelling of tree form"
    <http://mcfns.net/index.php/Journal/article/view/MCFNS7.1_2>.
    The models are parsimonious, describe well the tree bole shape
    over its full length, and are consistent with wood formation
    mechanisms through time.

Methods to estimate dynamic treatment regimes using Interactive
  Q-Learning, Q-Learning, weighted learning, and value-search methods based on 
  Augmented Inverse Probability Weighted Estimators and Inverse Probability
  Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for 
  Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., 
  Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.

Provides common functionality for the 'dynverse' packages. 
  'dynverse' is created to support the development, execution, and benchmarking of trajectory inference methods.
  For more information, check out <https://dynverse.org>.

Provides functionality to infer trajectories from single-cell data,
  represent them into a common format, and adapt them. Other biological information
  can also be added, such as cellular grouping, RNA velocity and annotation.
  Saelens et al. (2019) <doi:10.1038/s41587-019-0071-9>.

Scripting of structural equation models via 'lavaan' for
    Dyadic Data Analysis, and helper functions for supplemental
    calculations, tabling, and model visualization.  Current models
    supported include Dyadic Confirmatory Factor Analysis, the Actor–Partner 
    Interdependence Model (observed and latent), the Common Fate Model
    (observed and latent), Mutual Influence Model (latent), and the Bifactor
    Dyadic Model (latent).

It is used to identify dysregulated pathways based on a pre-ranked gene pair list. A fast algorithm is used to make the computation really fast. The data in package 'DysPIAData' is needed.