Title: Joint Modelling of Mixed Correlated Binary and Continuous
Author: Ehsan Bahrami Samani and Zhale Tahmasebinejad
Maintainer: Ehsan Bahrami Samani <ehsan_bahrami_samani@yahoo.com>
Description: A joint regression model for mixed correlated binary and
continuous responses is presented. In this model binary
response can be dependent on the continuous response. With this
model, the dependence between responses can be taken into
account by the correlation between errors in the models for

Description: Calculates bias, responsiveness, and other characteristics of
two-party electoral systems, with district-level electoral and
Packaged: Mon Sep 10 09:22:40 2007; king

Packaged: Mon Mar 17 16:42:45 2008; king

Packaged: Mon Aug 25 11:44:56 2008; king

Author: Andrew Gelman <gelman@stat.columbia.edu>, Gary King
<king@harvard.edu>, Andrew C. Thomas <acthomas@fas.harvard.edu>
Description: Calculates bias, responsiveness, and other characteristics
of two-party electoral systems, with district-level electoral
Packaged: Tue Aug 26 16:16:51 2008; king

Author: Andrew Gelman, Gary King and Andrew C. Thomas
Description: Examines two-party electoral systems and calculates
quantities of interest based on the behaviour of their

Title: JudgeIt: A Program for Evaluating Electoral Systems and

Description: Generates image data for fractals (Julia and Mandelbrot
sets) on the complex plane in the given region and resolution.

Authors@R: c(person("Mehmet", "Suzen", email = "mehmet.suzen@physics.org", role = c("aut", "cre")))
Description: Generates image data for fractals (Julia and Mandelbrot sets) on the complex plane in the given region and resolution.

Description: Generates image data for fractals (Julia and Mandelbrot sets) on the complex plane in the given region and resolution. Benoit B Mandelbrot (1982).

Title: Seamless Integration Between R and 'Julia'
Authors@R: person("Changcheng Li", email = "cxl508@psu.edu",
Description: Provides an R interface to 'Julia',
which is a high-level, high-performance dynamic programming language
for numerical computing, see <https://julialang.org/> for more information.
It provides a high-level interface as well as a low-level interface.
Using the high level interface, you could call any 'Julia' function just like
any R function with automatic type conversion. Using the low level interface,
you could deal with C-level SEXP directly while enjoying the convenience of
using a high-level programming language like 'Julia'.
SystemRequirements: Julia >= 0.5.0, RCall.jl
Packaged: 2017-11-16 18:45:02 UTC; lichangcheng