Description Objects from the Class Slots Extends Methods Author(s) See Also Examples

Objects holding the results of fitting multinomial procesing tree (MPT) models. `bmpt`

objects are fits to models which are member of L-BMPT (`bmpt.model-class`

; see also Purdy & Batchelder, 2009), `mpt`

objects to those binary MPTs that are not represented in a way that is compatible to L-BMPT.

Objects can be created by a call to `fit.mpt`

. They hold all information: the model as a model object, the data, and the results from the fitting (e.g., parameters, likelihood values,...).

`model`

:The model object, see

`bmpt.model-class`

`observed.data`

:Array. The data entered.

`predicted.data`

:Aray. The predicted data.

`C.matrix`

:A list holding the "C" matrices which contain the relative frequency of data per branch and tree.

`g2`

:Numeric. The G^2 value of the fitted model.

`logLikelihood`

:Numeric. The (-2*) Log-Likelihood of the fitted model.

`estimates`

:Matrix. The parameter estimates of the fitted model.

`multifit`

:Logical. Does the data contain more than one individual dataset?

`hessian`

:List of Hessian matrices

`default.ci`

:Numeric. Standard size of confidence intervals.

`typeHessian`

:List containing the type(s) of Hessian matrix. Can be either,

`"expected"`

or`"observed"`

. Only in class`bmpt`

.`hfail`

:Numeric. Did calculation of expected hessian fail (=1)? Only in class

`bmpt`

.`fia`

:List of Fisher Information Approximation results. Currently not implemented. Only in class

`bmpt`

.`parametric.ci`

:List containing the parametric bootstrapped confidence intervall. Not yet implemented. Only in class

`bmpt`

.`nonparametric.ci`

:List containing the parametric bootstrapped confidence intervall. Not yet implemented. Only in class

`bmpt`

.

`bmpt`

extends `mpt`

.

- show
`signature(object = "mpt")`

: Method for displaying overall results.- parameters
see

`parameters-methods`

- goodness.of.fit
`signature(object = "mpt")`

: Function to compute and display the (-2 *) Log-Likelihood, the G^2, the degrees of freedom and the p for the model fit.- information.criteria
`signature(object = "mpt")`

: Function to compute and display AIC, BIC, and (when computed) FIA.- default.ci
`signature(object = "mpt")`

: Accessor function for the default.ci slot. A replacement function exists as well!- observed.data
`signature(object = "mpt")`

: Accessor function for the observed data.- predicted.data
`signature(object = "mpt")`

: Accessor function for the predicted data.- logLikelihood
`signature(object = "mpt")`

: Accessor function for the (-2 *) Log-Likelihood of the fitted model.- estimates
`signature(object = "mpt")`

: Accesor function for the parameter estimates. This function returns the values of the fitted parameters (i.e., when inequality restrictions are present the parameters of the reparametrized model are presented)- check
`signature(object = "mpt")`

: Very informative function that returns a list with useful information of the fitted model:

Do probabilities sum to 1?; number of trees; number of categories; number of free parameters in the final model; names of free parameters in the final model; number of fixed parameters in the final model; names of fixed parameters in the final model; names of parameters in the initial model (i.e., no restrictions applied); maximum number of branches per category; vector with number of branches per category; degrees of freedom; is model a member of L-BMPT?

Henrik Singmann

1 | ```
showClass("bmpt")
``` |

MPTinR2 documentation built on May 31, 2017, 1:54 a.m.

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