Get Sunrise and Sunset Times for US Airport Locations
c(person("Sharon", "Machlis", email = "Rbook@machlis.com", role =  c("aut", "cre")))
Wrapper for a US Transportation Security Administration API.
API info: <https://www.dhs.gov/mytsa-api-documentation>
Includes helper functions to look up 3-letter codes for US airports.

Functions for drawing samples according to Sunter's
sampling design, and for computing first and second order
inclusion probabilities

Detecting Structural Change with Heteroskedasticity
c(
person(c("Muhammad", "Yaseen"),  email = "myaseen208@gmail.com", role = c("aut", "cre"))
, 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"))
)
Muhammad Yaseen [aut, cre],
Sami Ullah [aut, ctb],
Gulfam Haider [aut, ctb]
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>).

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

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.

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>.