Description Slots Extends Accessor Functions

A fitted `btmix`

model.

`model`

:A

`FLXMC`

object for a Bradley-Terry 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.

`flx.call`

:Internal call to

`stepFlexmix`

`nobs`

:Number of observations.

`labels`

:Labels of objects compared.

`mscale`

:Measurement scale of paired comparisons data.

`undecided`

:logical. Should an undecided parameter be estimated?

`ref`

:character or numeric. Which object parameter should be the reference category, i.e., constrained to zero?

`type`

:character. Should an auxiliary log-linear Poisson model or logistic binomial be employed for estimation? The latter is only available if not undecided effects are estimated.

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.

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