# TopicModelcontrol-class

From topicmodels v0.2-4
by Bettina Gruen

##### Different classes for controlling the estimation of topic models

Classes to control the estimation of topic models which are inheriting
from the virtual base class `"TopicModelcontrol"`

.

- Keywords
- classes

##### Objects from the Class

Objects can be created from named lists.

##### Slots

Class `"TopicModelcontrol"`

contains

`seed`

:- Object of class
`"integer"`

; used to set the seed in the external code for VEM estimation and to call`set.seed`

for Gibbs sampling. For Gibbs sampling it can also be set to`NA`

(default) to avoid changing the seed of the random number generator in the model fitting call. `verbose`

:- Object of class
`"integer"`

. If a positive integer, then the progress is reported every`verbose`

iterations. If 0 (default), no output is generated during model fitting. `save`

:- Object of class
`"integer"`

. If a positive integer the estimated model is saved all`verbose`

iterations. If 0 (default), no output is generated during model fitting. `prefix`

:- Object of class
`"character"`

; path indicating where to save the intermediate results. `nstart`

:- Object of class
`"integer"`

. Number of repeated random starts. `best`

:- Object of class
`"logical"`

; if`TRUE`

only the model with the maximum (posterior) likelihood is returned, by default equals`TRUE`

. `keep`

:- Object of class
`"integer"`

; if a positive integer, the log-likelihood is saved every`keep`

iterations. `estimate.beta`

:- Object of class
`"logical"`

; controls if beta, the term distribution of the topics, is fixed, by default equals`TRUE`

.

`"VEMcontrol"`

contains
`var`

:- Object of class
`"OPTcontrol"`

; controls the variational inference for a single document, by default`iter.max`

equals 500 and`tol`

10^-6. `em`

:- Object of class
`"OPTcontrol"`

; controls the variational EM algorithm, by default`iter.max`

equals 1000 and`tol`

10^-4. `initialize`

:- Object of class
`"character"`

; one of`"random"`

,`"seeded"`

and`"model"`

, by default equals`"random"`

.

`"LDAcontrol"`

extends class `"TopicModelcontrol"`

and
has the additional slots
`alpha`

:- Object of class
`"numeric"`

; initial value for alpha.

`"LDA_VEMcontrol"`

extends classes
`"LDAcontrol"`

and `"VEMcontrol"`

and has the
additional slots
`estimate.alpha`

:- Object of class
`"logical"`

; indicates if the parameter alpha is fixed a-priori or estimated, by default equals`TRUE`

.

`"LDA_Gibbscontrol"`

extends classes
`"LDAcontrol"`

and has the additional slots
`delta`

:- Object of class
`"numeric"`

; initial value for delta, by default equals 0.1. `iter`

:- Object of class
`"integer"`

; number of Gibbs iterations, by default equals 2000. `thin`

:- Object of class
`"integer"`

; number of omitted in-between Gibbs iterations, by default equals`iter`

. `burnin`

:- Object of class
`"integer"`

; number of omitted Gibbs iterations at beginning, by default equals 0. `burnin`

:- Object of class
`"integer"`

; number of omitted Gibbs iterations at beginning, by default equals 0. `initialize`

:- Object of class
`"character"`

; one of`"random"`

,`"beta"`

and`"z"`

, by default equals`"random"`

.

`"CTM_VEMcontrol"`

extends classes
`"TopicModelcontrol"`

and `"VEMcontrol"`

and has the
additional slots
`cg`

:- Object of class
`"OPTcontrol"`

; controls the conjugate gradient iterations in fitting the variational mean and variance per document, by default`iter.max`

equals 500 and`tol`

10^-5.

`"OPTcontrol"`

contains
`iter.max`

:- Object of class
`"integer"`

; maximum number of iterations. `tol`

:- Object of class
`"numeric"`

; tolerance for convergence check.

*Documentation reproduced from package topicmodels, version 0.2-4, License: GPL-2*

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