Implements a modern, unified estimation strategy for common 
	mediation estimands (natural effects, organic effects, interventional effects, 
	and recanting twins) in combination with modified treatment policies as 
	described in Liu, Williams, Rudolph, and Díaz (2024) 
	<doi:10.48550/arXiv.2408.14620>. Estimation makes use of recent advancements 
	in Riesz-learning to estimate a set of required nuisance parameters with 
	deep learning. The result is the capability to estimate mediation effects with 
	binary, categorical, continuous, or multivariate exposures with 
	high-dimensional mediators and mediator-outcome confounders using machine 
	learning.

The Crunch.io service <https://crunch.io/> provides a cloud-based
    data store and analytic engine, as well as an intuitive web interface.
    Using this package, analysts can interact with and manipulate Crunch
    datasets from within R. Importantly, this allows technical researchers to
    collaborate naturally with team members, managers, and clients who prefer a
    point-and-click interface.

Functions for reading in and manipulating CRU TS3.21: Climatic
    Research Unit (CRU) Time-Series (TS) Version 3.21 data.

In meta regression sometimes the studies have multiple effects that are correlated. For this reason cluster robust standard errors must be computed. However, since the clusters are unbalanced the wild bootstrap is suggested. See Oczkowski E. and Doucouliagos H. (2015). "Wine prices and quality ratings: a meta-regression analysis". American Journal of Agricultural Economics, 97(1): 103--121. <doi:10.1093/ajae/aau057> and Cameron A. C., Gelbach J. B. and Miller D. L. (2008). "Bootstrap-based improvements for inference with clustered errors". The Review of Economics and Statistics, 90(3): 414--427. <doi:10.1162/rest.90.3.414>.

To re-calculate the coefficients and the standard deviation when changing the reference group.

Reading and writing of files in the most commonly used formats of
  structural crystallography. It includes functions to work with a variety
  of statistics used in this field and functions to perform basic
  crystallographic computing. References: D. G. Waterman, J. Foadi, G. Evans 
  (2011) <doi:10.1107/S0108767311084303>.