wordfish: Estimate a Wordfish Model

In austin: A package for doing things with words

Description

Estimates a Wordfish model using Conditional Maximum Likelihood.

Usage

wordfish(wfm, dir=c(1, 10), control=list(tol=1e-06,
         sigma=3, startparams=NULL), verbose=FALSE)

Arguments

wfm	a word frequency matrix
dir	set global identification by forcing theta[dir[1]] < theta[dir[2]]
control	list of estimation options
verbose	produce a running commentary

Details

Fits a Wordfish model with document ideal points constrained to mean zero and unit standard deviation.

The control list specifies options for the estimation process. These are: tol, the proportional change in log likelihood sufficient to halt estimatioe, sigma the standard deviation for the beta prior in poisson form, and startparams a previously fitted wordfish model. verbose generates a running commentary during estimation

The model has two equivalent forms: a poisson model with two sets of document and two sets of word parameters, and a multinomial with two sets of word parameters and document ideal points. The first form is used for estimation, the second for summarizing and prediction.

The model is regularized by assuming a prior on beta with mean zero and standard deviation sigma (in poisson form). If you don't want to regularize, set beta to a large number.

Value

An object of class wordfish. This is a list containing:

dir	global identification of the dimension
theta	document positions
alpha	document fixed effects
beta	word slope parameters
psi	word fixed effects
docs	names of the documents
words	names of words
sigma	regularization parameter for betas in poisson form
ll	final log likelihood
se.theta	standard errors for document position
data	the original data

Author(s)

Will Lowe

References

Slapin and Proksch (2008) 'A Scaling Model for Estimating Time-Series Party Positions from Texts.' American Journal of Political Science 52(3):705-772.

See Also

plot.wordfish, summary.wordfish, coef.wordfish, fitted.wordfish, predict.wordfish, sim.wordfish

Examples

dd <- sim.wordfish()
wf <- wordfish(dd$Y)
summary(wf)

austin documentation built on May 2, 2019, 5:48 p.m.