Utilities for simulating and prototyping relational event models,
    including helpers to generate dynamic event sequences and covariate
    processes for sender and receiver sets. The endogenous-effect and
    case-control estimation machinery follows Juozaitiene and Wit (2024)
    <doi:10.1093/jrsssa/qnae132>.

Fits tractable fully parametric odds-based regression models for survival data, including proportional odds (PO), accelerated failure time (AFT), accelerated odds (AO), and General Odds (GO) models in overall survival frameworks. Given at least an R function specifying the survivor, hazard rate and cumulative distribution functions, any user-defined parametric distribution can be fitted. We applied and evaluated a minimum of seventeen (17) various baseline distributions that can handle different failure rate shapes for each of the four different proposed odds-based regression models. For more information see Bennet et al., (1983) <doi:10.1002/sim.4780020223>, and Muse et al., (2022) <doi:10.1016/j.aej.2022.01.033>.

A testing framework for testing the multivariate point null hypothesis. 
    A testing framework described in Elder et al. (2022) <arXiv:2203.01897> to test the multivariate point null hypothesis.  After the user selects a parameter of interest and defines the assumed data generating mechanism, this information should be encoded in functions for the parameter estimator and its corresponding influence curve. Some parameter and data generating mechanism combinations have codings in this package, and are explained in detail in the article.

Tools and functions to efficiently create datasets used in pharmacometric analysis.
  Additional functionality is added to create documentation and prepare files for submission and 
  quality control purposes.

The goal of 'amp.sim' is to transform 'NONMEM' models into R syntax so they can be used for
    simulations using the 'deSolve', 'nlmixr2' or 'mrgsolve' package. Additionally, functionality is included to aid simulations performed
    directly in 'NONMEM' and to automatically create shiny apps for simulation models.