Time series of four different power loss modes can be calculated based on obtained Isc-Voc curves.
Abdulkerim Gok [aut, ctb] (<https://orcid.org/0000-0003-3433-7106>),

Title: Get Sunrise and Sunset Times for US Airport Locations
Authors@R: c(person("Sharon", "Machlis", email = "Rbook@machlis.com", role =  c("aut", "cre")))
Description: Wrapper for a US Transportation Security Administration API.
Includes helper functions to look up 3-letter codes for US airports.

Author: Alessandro Barbiero, Giancarlo Manzi
Description: Functions for drawing samples according to Sunter's
sampling design, and for computing first and second order

Packaged: 2012-05-03 20:10:14 UTC; Alessandro

Title: Detecting Structural Change with Heteroskedasticity
, person(c("Sami", "Ullah"),  email = "samiullahuos@gmail.com", role = c("aut", "ctb"))
, person(c("Gulfam", "Haider"),  email = "haider.gulfam786@gmail.com", role = c("aut", "ctb"))
Description: Calculates the sup MZ value to detect the unknown structural break points under Heteroskedasticity as given in Ahmed et al. (2017) (<DOI: 10.1080/03610926.2016.1235200>).

Title: Exact Test and Visualization of Multi-Set Intersections
Contact: Minghui Wang <minghui.wang@mssm.edu>, Bin Zhang
Description: Efficient statistical testing and scalable visualization of intersections among multiple sets.

Description: Identification of sets of objects with shared features is a common operation in all disciplines. Analysis of intersections among multiple sets is fundamental for in-depth understanding of their complex relationships. This package implements a theoretical framework for efficient computation of statistical distributions of multi-set intersections based upon combinatorial theory, and provides multiple scalable techniques for visualizing the intersection statistics. The statistical algorithm behind this package was published in Wang et al (2015), doi:10.1038/srep16923.

Description: Identification of sets of objects with shared features is a common operation in all disciplines. Analysis of intersections among multiple sets is fundamental for in-depth understanding of their complex relationships. This package implements a theoretical framework for efficient computation of statistical distributions of multi-set intersections based upon combinatorial theory, and provides multiple scalable techniques for visualizing the intersection statistics. The statistical algorithm behind this package was published in Wang et al. (2015) <doi:10.1038/srep16923>.