Supports calculations and visualization for renewable power systems and the environment. Analysis and graphical tools for DC and AC circuits and their use in electric power systems. Analysis and graphical tools for thermodynamic cycles and heat engines, supporting efficiency calculations in coal-fired power plants, gas-fired power plants. Calculations of carbon emissions and atmospheric CO2 dynamics. Analysis of power flow and demand for the grid, as well as power models for microgrids and off-grid systems. Provides resource and power generation for hydro power, wind power, and solar power.

Provides an R interface to the NCBI's 'EUtils' API, 
    allowing users to search databases like 'GenBank' 
    <https://www.ncbi.nlm.nih.gov/genbank/> and 'PubMed' 
    <https://pubmed.ncbi.nlm.nih.gov/>, process the 
    results of those searches and pull data into their R sessions.

A dependency management toolkit for R. Using 'renv', you can create
    and manage project-local R libraries, save the state of these libraries to
    a 'lockfile', and later restore your library as required. Together, these
    tools can help make your projects more isolated, portable, and reproducible.

Provides a general routine, envMU, which allows  estimation of the M envelope of span(U) given root n consistent estimators of M and U. The routine envMU does not presume a model.  This package implements response envelopes,  partial response envelopes,  envelopes in the predictor space,  heteroscedastic envelopes,  simultaneous envelopes,  scaled response envelopes,  scaled envelopes in the predictor space,  groupwise envelopes, weighted envelopes,  envelopes in logistic regression, envelopes in Poisson regression envelopes in function-on-function linear regression, envelope-based Partial Partial Least Squares,  envelopes with non-constant error covariance, envelopes with t-distributed errors, reduced rank envelopes and reduced rank envelopes with non-constant error covariance. For each of these model-based routines the package provides inference tools including bootstrap, cross validation, estimation and prediction, hypothesis testing on coefficients are included except for weighted envelopes. Tools for selection of dimension include AIC, BIC and likelihood ratio testing.   Background is available at Cook, R. D., Forzani, L. and Su, Z. (2016) <doi:10.1016/j.jmva.2016.05.006>. Optimization is based on a clockwise coordinate descent algorithm.