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 and intuitive framework for building interactive data
    analysis pipelines. You add R functions one by one, and 'pipeflow'
    wires them into a pipeline that stays consistent as you go. Modify,
    remove, or insert steps at any stage, manage all parameters in one
    place, fast execution (C++-powered DAG) for interactive use and Shiny
    backends.

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.

Provides various styles of function chaining methods: Pipe
    operator, Pipe object, and pipeline function, each representing a distinct
    pipeline model yet sharing almost a common set of features: A value can be
    piped to the first unnamed argument of a function and to dot symbol in an
    enclosed expression. The syntax is designed to make the pipeline more
    readable and friendly to a wide range of operations.

Enable users to measure and record the execution time of pipe operations (using |>) with optional logging to dataframes and output to the console.

An interface to compute poverty and inequality 
    indicators for more than 160 countries and regions from the World
    Bank's database of household surveys, through the 
    Poverty and Inequality Portal (PIP).

An embedded proximal interior point quadratic programming solver, which can solve dense and sparse quadratic programs, described in Schwan, Jiang, Kuhn, and Jones (2023) <doi:10.48550/arXiv.2304.00290>. Combining an infeasible interior point method with the proximal method of multipliers, the algorithm can handle ill-conditioned convex quadratic programming problems without the need for linear independence of the constraints. The solver is written in header only 'C++ 14' leveraging the 'Eigen' library for vectorized linear algebra. For small dense problems, vectorized instructions and cache locality can be exploited more efficiently. Allocation free problem updates and re-solves are also provided.