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pscl (version 0.95)

Political Science Computational Laboratory, Stanford University

Description

Bayesian analysis of item-response theory (IRT) models, roll call analysis; computing highest density regions; maximum likelihood estimation of zero-inflated and hurdle models for count data; goodness-of-fit measures for GLMs; data sets used in writing and teaching at the Political Science Computational Laboratory; seats-votes curves.

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Version

Install

install.packages('pscl')

Monthly Downloads

27,194

Version

0.95

License

GPL-2

Maintainer

Simon Jackman

Last Published

January 31st, 2024

Functions in pscl (0.95)

igamma

inverse-Gamma distribution
ca2006

California Congressional Districts in 2006
bioChemists

article production by graduate students in biochemistry Ph.D. programs
dropUnanimous

drop unanimous votes from rollcall objects and matrices
admit

Applications to a Political Science PhD Program
hurdle.control

Control Parameters for Hurdle Count Data Regression
convertCodes

convert entries in a rollcall matrix to binary form
betaHPD

compute and optionally plot beta HDRs
ntable

nicely formatted tables
hurdle

Hurdle Models for Count Data Regression
AustralianElections

elections to Australian House of Representatives, 1949-2004
predict.hurdle

Methods for hurdle Objects
computeMargins

add information about voting outcomes to a rollcall object
plot.predict.ideal

plot methods for predictions from ideal objects
plot.seatsVotes

plot seats-votes curves
constrain.legis

constrain legislators' ideal points in analysis of roll call data
partycodes

political parties appearing in the U.S. Congress
s109

rollcall object, 109th U.S. Senate
constrain.items

constrain item parameters in analysis of roll call data
hitmiss

Table of Actual Outcomes against Predicted Outcomes for discrete data models
extractRollCallObject

return the roll call object used in fitting an ideal model
postProcess

remap MCMC output via affine transformations
predprob.glm

Predicted Probabilties for GLM Fits
predprob

compute predicted probabilities from fitted models
predict.zeroinfl

Methods for zeroinfl Objects
predprob.ideal

predicted probabilities from fitting ideal to rollcall data
summary.rollcall

summarize a rollcall object
ideal

analysis of educational testing data and roll call data with IRT models, via Markov chain Monte Carlo methods
sc9497

votes from the United States Supreme Court, from 1994-1997
pR2

compute various pseduo-R2 measures
hurdletest

Testing for the Presence of a Zero Hurdle
unionDensity

cross national rates of trade union density
state.info

information about the American states needed for U.S. Congress
readKH

read roll call data in Poole-Rosenthal KH format
summary.ideal

summary of an ideal object
tracex

trace plot of MCMC iterates, posterior density of legislators' ideal points
zeroinfl

Zero-inflated Count Data Regression
seatsVotes

A class for creating seats-votes curves
prussian

Prussian army horse kick data
simpi

Monte Carlo estimate of pi (3.14159265...)
zeroinfl.control

Control Parameters for Zero-inflated Count Data Regression
absentee

Absentee and Machine Ballots in Pennsylvania State Senate Races
idealToMCMC

convert an object of class ideal to a coda MCMC object
odTest

likelihood ratio test for over-dispersion in count data
plot.ideal

plots an ideal object
vectorRepresentation

convert roll call matrix to series of vectors
dropRollCall

drop user-specified elements from a rollcall object
predict.ideal

predicted probabilities from an ideal object
rollcall

create an object of class rollcall
vuong

Vuong's non-nested hypothesis test