person("Dror", "Bogin", email = "dror.bogin@gmail.com",role = c("aut", "cre"))
Allows the user to compare SIRI (Service Interface for Real Time Information) data sets to their GTFS (General Transit Feed Specification) counterparts, a "Request_id" column us needed for the SIRI data frame in order to subset parts of it for use.

Compartmental Susceptible-Infectious-Recovered (SIR) Model of
Community and Household Infection
We build an Susceptible-Infectious-Recovered (SIR) model where the rate of infection is the sum of the household rate and the community rate. We estimate the posterior distribution of the parameters using the Metropolis algorithm. Further details may be found in: F Scott Dahlgren, Ivo M Foppa, Melissa S Stockwell, Celibell Y Vargas, Philip LaRussa, Carrie Reed (2021) "Household transmission of influenza A and B within a prospective cohort during the 2013-2014 and 2014-2015 seasons" <doi:10.1002/sim.9181>.

Sliced Inverse Regression with Thresholding
c(person("Clement", "Weinreich", role = c("aut", "cre"),
email = "clement@weinreich.fr"),
person("Jerome", "Saracco", role = c("aut")),
person("Hadrien", "Lorenzo", role = c("aut")))
Clement Weinreich [aut, cre],
Jerome Saracco [aut],
Hadrien Lorenzo [aut]
Implements a thresholded version of the Sliced Inverse Regression method, which
allows to do variable selection.

Jianqing Fan, Yang Feng, Richard Samworth, Yichao Wu
(Iterative) Sure Independent Screening for Generalized
Linear Models and Cox's Proportional Hazard's Models

(Iterative) Sure Independence Screening for Generalized
Linear Models and Cox's Proportional Hazard's Models

(Iterative) Sure Independence Screening for Generalized
Linear Models and Cox's Proportional Hazards Models

Jianqing Fan, Yang Feng,  Diego Franco Saldana, Richard Samworth,  Yichao Wu
(Iterative) Sure Independence Screening for Generalized Linear Models and Cox's Proportional Hazards Models

Variable selection techniques are essential tools for model selection and estimation in high-dimensional statistical models. Through this publicly available package, we provide a unified environment to carry out variable selection using iterative sure independence screening (SIS) and all of its variants in generalized linear models and the Cox proportional hazards model.