Provides fundamental abstractions for doing asynchronous
    programming in R using promises. Asynchronous programming is useful
    for allowing a single R process to orchestrate multiple tasks in the
    background while also attending to something else. Semantics are
    similar to 'JavaScript' promises, but with a syntax that is idiomatic
    R.

A comprehensive, user-friendly package for label-free proteomics data analysis and machine learning-based modeling. Data generated from 'MaxQuant' can be easily used to conduct differential expression analysis, build predictive models with top protein candidates, and assess model performance. promor includes a suite of tools for quality control, visualization, missing data imputation (Lazar et. al. (2016) <doi:10.1021/acs.jproteome.5b00981>), differential expression analysis (Ritchie et. al. (2015) <doi:10.1093/nar/gkv007>), and machine learning-based modeling (Kuhn (2008) <doi:10.18637/jss.v028.i05>).

Deploy, maintain, and invoke predictive models using the 'Alteryx
    Promote' REST API.  'Alteryx Promote' is available at the URL:
    <https://www.alteryx.com/products/alteryx-promote>.

Analysis and measurement of promotion effectiveness on a given target variable (e.g. daily sales). After converting promotion schedule into dummy or smoothed predictor variables, the package estimates the effects of these variables controlled for trend/periodicity/structural change using prophet by Taylor and Letham (2017) <doi:10.7287/peerj.preprints.3190v2> and some prespecified variables (e.g. start of a month).

Set the 'R' prompt dynamically, from a function. The package
    contains some examples to include various useful dynamic information
    in the prompt: the status of the last command (success or failure);
    the amount of memory allocated by the current 'R' process; the name of
    the R package(s) loaded by 'pkgload' and/or 'devtools'; various 'git'
    information: the name of the active branch, whether it is dirty,
    if it needs pushes pulls. You can also create your own prompt if you
    don't like the predefined examples.