A fitted raschmix
model.
model
:A FLXMC
object for a Rasch mixture
model
prior
:Numeric vector with prior probabilities of classes.
posterior
:Named list with elements scaled
and unscaled
, both matrices with one row per observation
and one column per class.
iter
:Number of EM iterations.
k
:Number of classes after EM.
k0
:Number of classes at start of EM.
cluster
:Class assignments of observations.
size
:Class sizes.
logLik
:Log-likelihood at EM convergence.
df
:Total number of parameters of the model.
components
:List describing
the fitted components using FLXcomponent
objects.
formula
:Object of class "formula"
.
control
:Object of class "FLXcontrol"
.
call
:The function call used to create the object.
group
:Object of class "factor"
.
converged
:Logical, TRUE
if EM algorithm converged.
concomitant
:Object of class "FLXP"
..
weights
:Optional weights of the observations.
scores
:Type of score model employed.
restricted
:Logical. Is the score model equal across components?
deriv
:Type of derivatives used for computing
gradient and Hessian matrix. Analytical with sum algorithm ("sum"
),
analytical with difference algorithm ("diff"
, faster but numerically unstable),
or numerical.
extremeScoreProbs
:Estimated probability of solving either all or no items.
rawScoresData
:Table of raw scores from the data.
flx.call
:Internal call to stepFlexmix
nobs
:Number of observations without missing values, excluding observations with an extreme score.
identified.items
:Factor indicating which items are identified.
Class flexmix
, directly.
The following functions should be used for accessing the corresponding slots:
clusters
:Cluster assignments of observations.
posterior
:A matrix of posterior probabilities for each observation.