PLNmixturefamily | R Documentation |

The function `PLNmixture()`

produces an instance of this class.

This class comes with a set of methods, some of them being useful for the user:
See the documentation for `getBestModel()`

, `getModel()`

and `plot()`

.

`PLNmodels::PLNfamily`

-> `PLNmixturefamily`

`clusters`

vector indicating the number of clusters considered is the successively fitted models

`new()`

helper function for forward smoothing: split a group

Initialize all models in the collection.

PLNmixturefamily$new( clusters, responses, covariates, offsets, formula, control )

`clusters`

the dimensions of the successively fitted models

`responses`

the matrix of responses common to every models

`covariates`

the matrix of covariates common to every models

`offsets`

the matrix of offsets common to every models

`formula`

model formula used for fitting, extracted from the formula in the upper-level call

`control`

a list for controlling the optimization. See details.

`control`

a list for controlling the optimization. See details.

`optimize()`

Call to the optimizer on all models of the collection

PLNmixturefamily$optimize(config)

`config`

a list for controlling the optimization

`smooth()`

function to restart clustering to avoid local minima by smoothing the loglikelihood values as a function of the number of clusters

PLNmixturefamily$smooth(control)

`control`

a list to control the smoothing process

`plot()`

Lineplot of selected criteria for all models in the collection

PLNmixturefamily$plot(criteria = c("loglik", "BIC", "ICL"), reverse = FALSE)

`criteria`

A valid model selection criteria for the collection of models. Any of "loglik", "BIC" or "ICL" (all).

`reverse`

A logical indicating whether to plot the value of the criteria in the "natural" direction (loglik - 0.5 penalty) or in the "reverse" direction (-2 loglik + penalty). Default to FALSE, i.e use the natural direction, on the same scale as the log-likelihood..

A `ggplot2`

object

`plot_objective()`

Plot objective value of the optimization problem along the penalty path

PLNmixturefamily$plot_objective()

a `ggplot`

graph

`getBestModel()`

Extract best model in the collection

PLNmixturefamily$getBestModel(crit = c("BIC", "ICL", "loglik"))

`crit`

a character for the criterion used to performed the selection. Either "BIC", "ICL" or "loglik". Default is

`ICL`

a `PLNmixturefit`

object

`show()`

User friendly print method

PLNmixturefamily$show()

`print()`

User friendly print method

PLNmixturefamily$print()

`clone()`

The objects of this class are cloneable with this method.

PLNmixturefamily$clone(deep = FALSE)

`deep`

Whether to make a deep clone.

The function `PLNmixture`

, the class `PLNmixturefit`

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