Measure productivity and efficiency using Data Envelopment Analysis 
    (DEA). Available methods include DEA under different technology assumptions, 
    bootstrapping of efficiency scores and calculation of the Malmquist 
    productivity index. Analyses can be performed either in the console or with 
    the provided 'shiny' app. See Banker, R.; Charnes, A.; Cooper, W.W. (1984)
    <doi:10.1287/mnsc.30.9.1078>, Färe, R.; Grosskopf, S. (1996) <doi:10.1007/978-94-009-1816-0>.

Implements the Product of Independent beta Probabilities dose Escalation (PIPE) design for dual-agent Phase I trials as described in Mander AP, Sweeting MJ (2015) <DOI:10.1002/sim.6434>.

Provides a simple function to bind a piped object to a placeholder
    symbol to enable complex function evaluation with the base R |> pipe.

To take nested function calls and convert them to a more readable form using pipes from package 'magrittr'.

A lightweight yet powerful framework for building robust data
    analysis pipelines. With 'pipeflow', you initialize a pipeline with your
    dataset and construct workflows step by step by adding R functions.
    You can modify, remove, or insert steps and parameters at any stage,
    while 'pipeflow' ensures the pipeline's integrity.
    Overall, this package offers a beginner-friendly framework that simplifies
    and streamlines the development of data analysis pipelines by making
    them modular, intuitive, and adaptable.

A framework for defining 'pipelines' of functions for applying data transformations, 
  model estimation and inverse-transformations, resulting in predicted value generation (or 
  model-scoring) functions that automatically apply the entire pipeline of functions required to go
  from input to predicted output.

Functions representing some useful empirical and data-driven
    models of heat loss, corrosion diagnostics, reliability and predictive
    maintenance of pipeline systems. The package is an option for technical
    engineering departments of heat generating and heat transfer companies
    that use or plan to use regulatory calculations in their activities.
    Methods are described in
    Timashev et al. (2016) <doi:10.1007/978-3-319-25307-7>,
    A.C.Reddy (2017) <doi:10.1016/j.matpr.2017.07.081>,
    Minenergo (2008) <https://docs.cntd.ru/document/902148459>,
    Minenergo (2005) <https://docs.cntd.ru/document/1200035568>,
    Xing LU. (2014) <doi:10.1080/23744731.2016.1258371>.