Implement the statistical test proposed in Weng et al. (2021) to test whether
    the average treatment effect curve is constant and whether a discrete covariate is a significant effect modifier.

Fits (longitudinal) dose-response models utilizing a Bayesian model
  averaging approach as outlined in Gould (2019) <doi:10.1002/bimj.201700211>
  for both continuous and binary responses.  Functions
  for plotting and calculating various posterior quantities
  (e.g. posterior mean, quantiles, probability of minimum efficacious dose,
  etc.) are also implemented.  Copyright Eli Lilly and Company (2019).

Set of tools to facilitate package development and make R a more user-friendly place. Mostly for developers (or anyone who writes/shares functions). Provides a simple, powerful and flexible way to check the arguments passed to functions. 
    The developer can easily describe the type of argument needed. If the user provides a wrong argument, then an informative error message is prompted with the requested type and the problem clearly stated--saving the user a lot of time in debugging.

A penalized/non-penalized implementation for dynamic regression in the presence of autocorrelated residuals (DREGAR) using iterative penalized/ordinary least squares. It applies Mallows CP, AIC, BIC and GCV to select the tuning parameters.

An implementation of distributional random forests as introduced in Cevid & Michel & Meinshausen & Buhlmann (2020) <arXiv:2005.14458>.

Fit restricted mean models for the conditional association
  between an exposure and an outcome, given covariates. Three methods
  are implemented: O-estimation, where a nuisance model for the
  association between the covariates and the outcome is used;
  E-estimation where a nuisance model for the association
  between the covariates and the exposure is used, and doubly robust (DR)
  estimation where both nuisance models are used. In DR-estimation,
  the estimates will be consistent when at least one of the nuisance
  models is correctly specified, not necessarily both. For more information, see Zetterqvist and Sjölander (2015) <doi:10.1515/em-2014-0021>.