Provides a summary of the output from ideal point estimation contained
in an object of class ideal
.
1 2 3 4 5 
object 
an object of class 
prob 
scalar, a proportion between 0 and 1, the content of the highest posterior density (HPD) interval to compute for the parameters 
burnin 
of the recorded MCMC samples, how many to discard as
burnin? Default is 
sort 
logical, default is 
include.beta 
whether or not to calculate summary statistics of
beta, if beta is available. If the item parameters were not stored
in the 
... 
further arguments passed to or from other functions 
The test of whether a given discrimination parameter is
distinguishible from zero first checks to see if the two most extreme
quantiles
are symmetric around .5 (e.g., as are the default
value of .025 and .975). If so, the corresponding quantiles of the
MCMC samples for each discrimination parameter are inspected to see if
they have the same sign. If they do, then the corresponding
discrimination parameter is flagged as distinguishible from zero;
otherwise not.
An item of class summary.ideal
with elements:
object 
the name of the ideal object as an

xm 

xsd 

xHDR 

bm 

bsd 

bHDR 

bSig 
a 
party.quant 
if party information is available through the

When specifying a value of burnin
different from that used
in fitting the ideal
object, note a distinction
between the iteration numbers of the stored iterations, and the
number of stored iterations. That is, the n
th iteration
stored in an ideal
object will not be iteration
n
if the user specified thin>1
in the call to
ideal
. Here, iterations are tagged with their
iteration number. Thus, if the user called ideal
with
thin=10
and burnin=100
then the stored iterations are
numbered 100, 110, 120, ...
. Any future subsetting via a
burnin
refers to this iteration number.
Simon Jackman jackman@stanford.edu
ideal
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24  f < system.file("extdata","id1.rda",package="pscl")
load(f)
summary(id1)
## Not run:
data(s109)
cl2 < constrain.legis(s109,
x=list("KENNEDY (D MA)"=c(1,0),
"ENZI (R WY)"=c(1,0),
"CHAFEE (R RI)"=c(0,.5)),
d=2)
id2Constrained < ideal(s109,
d=2,
priors=cl2, ## priors (w constraints)
startvals=cl2, ## start value (w constraints)
store.item=TRUE,
maxiter=5000,
burnin=500,
thin=25)
summary(id2Constrained,
include.items=TRUE)
## End(Not run)

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