Title: Performance Loss Rate Analysis Pipeline
person("Alan", "Curran", email = "alan.curran@case.edu", role = c("aut", "cre"),
person("Tyler", "Burleyson", email = "tyler.burleyson@case.edu", role = "aut",
person("Sascha", "Lindig", email = "Sascha.Lindig@eurac.edu", role = "aut",
person("David", "Moser", email = "david.moser@eurac.edu", role = "aut",
person("Roger", "French", email = "roger.french@case.edu", role = "aut",
person(given = "Solar Durability and Lifetime Extension research center",
Description: The pipeline contained in this package provides tools used in the
Solar Durability and Lifetime Extension Center (SDLE) for the analysis of
Performance Loss Rates (PLR) in real world photovoltaic systems. Functions
included allow for data cleaning, feature correction, power predictive modeling,
PLR determination, and uncertainty bootstrapping through various methods
The vignette "Pipeline Walkthrough" gives
an explicit run through of typical package usage.
This material is based upon work supported by the U.S Department
of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under
Solar Energy Technologies Office (SETO) Agreement Number DE-EE-0008172.
This work made use of the High Performance Computing Resource in the
Core Facility for Advanced Research Computing at
Imports: dplyr (>= 0.7.8), magrittr (>= 1.5), broom (>= 0.5.1), ggplot2
Author: Alan Curran [aut, cre] (<https://orcid.org/0000-0002-4505-8359>),
Solar Durability and Lifetime Extension research center [cph, fnd]

person("Alan", "Curran", email = "alan.curran@case.edu", role = c("aut"),
person("William", "Oltjen", email = "william.oltjen@case.edu", role = c("aut"),
person("Roger", "French", email = "roger.french@case.edu", role = c("aut", "cre"),
0.3.1), segmented, forecast, scales, zoo
Author: Alan Curran [aut] (<https://orcid.org/0000-0002-4505-8359>),

Title: Time Series Regression Using the Power Weighted Densities (PWD)
Authors@R: c( person("Daniel", "McCarthy", role=c("aut","cre","ctb"),
Description: Contains functions which allow the user to perform time series regression quickly using the Power Weighted Densities (PWD) approach. alphahat_LR_one_Rcpp() is the main workhorse function within this package.
Imports: Rcpp (>= 0.11.5), stats, graphics