Rehnquist

<p>This dataframe contains a matrix of votes cast by U.S. Supreme Court
justices by all cases in the 1994-2004 terms.</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

Rehnquist function

<p>The dataframe has contains data for justices Rehnquist, Stevens,
O'Connor, Scalia, Kennedy, Souter, Thomas, Ginsburg, and Breyer for the
1994-2004 terms of the U.S. Supreme Court.  The dataframe also contains the
term of the case, and a time variable that counts from term 1 to 11.  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, Rehnquist Court (1994-2004) — Rehnquist

U.S. Supreme Court Vote Matrix, Rehnquist Court (1994-2004)

Rehnquist: U.S. Supreme Court Vote Matrix, Rehnquist Court (1994-2004)

Description

Arguments

Format