summaries  R Documentation 
Obtain the coefficients, model summary or coefficient variancecovariance
matrix for a model fitted by PlackettLuce
.
## S3 method for class 'PlackettLuce' coef(object, ref = 1L, log = TRUE, type = "all", ...) ## S3 method for class 'PlackettLuce' summary(object, ref = 1L, ...) ## S3 method for class 'PlackettLuce' vcov(object, ref = 1L, type = c("expected", "observed"), ...)
object 
An object of class "PlackettLuce" as returned by

ref 
An integer or character string specifying the reference item (for
which log worth will be set to zero). If 
log 
A logical indicating whether to return parameters on the log scale
with the item specified by 
type 
For 
... 
additional arguments, passed to 
By default, parameters are returned on the log scale, as most suited for
inference. If log = FALSE
, the worth parameters are returned,
constrained to sum to one so that they represent the probability that
the corresponding item comes first in a ranking of all items, given that
first place is not tied.
The variancecovariance matrix is returned for the worth and tie parameters
on the log scale, with the reference as specified by ref
. For models
estimated by maximum likelihood, the variancecovariance is the inverse of
the Fisher information of the loglikelihood.
For models with a normal or gamma prior, the variancecovariance is based on
the Fisher information of the logposterior. When adherence parameters have
been estimated, the logposterior is not linear in the parameters. In this
case there is a difference between the expected and observed Fisher
information. By default, vcov
will return the variancecovariance
based on the expected information, but type
gives to option to use
the observed information instead. For large samples, the difference between
these options should be small. Note that the estimation of the adherence
parameters is accounted for in the computation of the variancecovariance
matrix, but only the submatrix corresponding to the worth and tie
parameters is estimated.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.