anominate (version 0.6)

norm_anom: alpha-NOMINATE Estimate, Simulated Roll Call Matrix using Normal Utility

Description

alpha-NOMINATE estimates from simulated roll call matrix using normal utility. Estimates in one dimension.

Usage

data(norm_anom)

Value

An object of class anominate, a list with the following elements:

alpha

An object of class mcmc with the sampled values of the alpha parameter

beta

An object of class mcmc with the sampled values of the beta parameter

legislators

A object of class mcmc with the sampled values of the legislator ideal points, with each dimension stored in a separate list (e.g., the first dimension coordinates are stored in legislators[[1]], the second dimension coordinates in legislators[[2]], etc.)

yea.locations

A object of class mcmc with the sampled values of the Yea locations (midpoint - spread in W-NOMINATE) for each vote, with each dimension stored in a separate list (e.g., the first dimension coordinates are stored in yea.locations[[1]], the second dimension coordinates in yea.locations[[2]], etc.)

nay.locations

A object of class mcmc with the sampled values of the Nay locations (midpoint + spread in W-NOMINATE) for each vote, with each dimension stored in a separate list (e.g., the first dimension coordinates are stored in nay.locations[[1]], the second dimension coordinates in nay.locations[[2]], etc.)

wnom.result

An object of class nomObject with the W-NOMINATE results

References

Carroll, Royce, Jeffrey B. Lewis, James Lo, Keith T. Poole and Howard Rosenthal. 2013. ``The Structure of Utility in Spatial Models of Voting.'' American Journal of Political Science 57(4): 1008--1028.

See Also

'anominate.sim','anominate','summary.anominate','plot.anominate','densplot.anominate','traceplot.anominate'.

Examples

# NOT RUN {
# }
# NOT RUN {
# }
# NOT RUN {
normal.data <- anominate.sim(utility="normal") 
norm_anom <- anominate(normal.data, dims=1, polarity=2, nsamp=200, thin=1, 
	burnin=100, random.starts=FALSE, verbose=TRUE)
summary(norm_anom)
# }
# NOT RUN {
# }