SupremeCourt

<p>This dataframe contains a matrix votes cast by U.S. Supreme Court justices
in all cases in the 2000 term.</p>

datasets

Contains functions to perform Bayesian
inference using posterior simulation for a number of
statistical models. Most simulation is done in compiled C++
written in the Scythe Statistical Library Version 1.0.3. All
models return 'coda' mcmc objects that can then be summarized
using the 'coda' package. Some useful
utility functions such as density functions,
pseudo-random number generators for statistical
distributions, a general purpose Metropolis sampling algorithm,
and tools for visualization are provided.

Jong Hee Park

MCMCpack

Markov Chain Monte Carlo (MCMC) Package

Ghislain Vieilledent

Michael Malecki

Matthew Blackwell

Keith Poole

Craig Reed

Ben Goodrich

Qiushi Yu

Ross Ihaka

Pierre L'Ecuyer

Makoto Matsumoto

Takuji Nishimura

SupremeCourt function

<p>The dataframe has contains data for justices Rehnquist, Stevens,
O'Connor, Scalia, Kennedy, Souter, Thomas, Ginsburg, and Breyer for the 2000
term of the U.S. Supreme Court.  It contains data from 43 non-unanimous
cases. The votes are coded liberal (1) and conservative (0) using the
protocol of Spaeth (2003).  The unit of analysis is the case citation
(ANALU=0).  We are concerned with formally decided cases issued with written
opinions, after full oral argument and cases decided by an equally divided
vote (DECTYPE=1,5,6,7).</p>

Format

U.S. Supreme Court Vote Matrix — SupremeCourt

U.S. Supreme Court Vote Matrix

SupremeCourt: U.S. Supreme Court Vote Matrix

Description

Arguments

Format