PLNmixturefamily: An R6 Class to represent a collection of PLNmixturefit

In PLNmodels: Poisson Lognormal Models

An R6 Class to represent a collection of PLNmixturefit

Description

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().

Super class

PLNmodels::PLNfamily -> PLNmixturefamily

Active bindings

clusters

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

Methods

Public methods

• PLNmixturefamily$new()

• PLNmixturefamily$optimize()

• PLNmixturefamily$smooth()

• PLNmixturefamily$plot()

• PLNmixturefamily$plot_objective()

• PLNmixturefamily$getBestModel()

• PLNmixturefamily$show()

• PLNmixturefamily$print()

• PLNmixturefamily$clone()

Inherited methods

• PLNmodels::PLNfamily$getModel()
• PLNmodels::PLNfamily$postTreatment()

---

Method new()

helper function for forward smoothing: split a group

Initialize all models in the collection.

Usage

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

Arguments

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.

---

Method optimize()

Call to the optimizer on all models of the collection

Usage

PLNmixturefamily$optimize(config)

Arguments

config

a list for controlling the optimization

---

Method smooth()

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

Usage

PLNmixturefamily$smooth(control)

Arguments

control

a list to control the smoothing process

---

Method plot()

Lineplot of selected criteria for all models in the collection

Usage

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

Arguments

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..

Returns

A ggplot2::ggplot object

---

Method plot_objective()

Plot objective value of the optimization problem along the penalty path

Usage

PLNmixturefamily$plot_objective()

Returns

a ggplot2::ggplot graph

---

Method getBestModel()

Extract best model in the collection

Usage

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

Arguments

crit

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

Returns

a PLNmixturefit object

---

Method show()

User friendly print method

Usage

PLNmixturefamily$show()

---

Method print()

User friendly print method

Usage

PLNmixturefamily$print()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PLNmixturefamily$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

The function PLNmixture, the class PLNmixturefit

PLNmodels documentation built on April 4, 2025, 2:30 a.m.