super class for PLNPCAfamily and PLNnetworkfamily.

See also

Public fields

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

weights

the vector of observation weights

inception

a PLNfit object, obtained when no sparsifying penalty is applied.

models

a list of PLNfit object, one per penalty.

Active bindings

criteria

a data frame with the values of some criteria (approximated log-likelihood, BIC, ICL, etc.) for the collection of models / fits BIC and ICL are defined so that they are on the same scale as the model log-likelihood, i.e. with the form, loglik - 0.5 penalty

convergence

sends back a data frame with some convergence diagnostics associated with the optimization process (method, optimal value, etc)

Methods


Method new()

Create a new PLNfamily object.

Usage

PLNfamily$new(responses, covariates, offsets, weights, control)

Arguments

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

weights

the vector of observation weights

control

list controlling the optimization and the model

Returns

A new PLNfamily object


Method postTreatment()

Update fields after optimization

Usage

PLNfamily$postTreatment(config_post, config_optim)

Arguments

config_post

a list for controlling the post-treatments (optional bootstrap, jackknife, R2, etc.).

config_optim

a list for controlling the optimization parameters used during post_treatments


Method getModel()

Extract a model from a collection of models

Usage

PLNfamily$getModel(var, index = NULL)

Arguments

var

value of the parameter (rank for PLNPCA, sparsity for PLNnetwork) that identifies the model to be extracted from the collection. If no exact match is found, the model with closest parameter value is returned with a warning.

index

Integer index of the model to be returned. Only the first value is taken into account.

Returns

A PLNfit object


Method plot()

Lineplot of selected criteria for all models in the collection

Usage

PLNfamily$plot(criteria, reverse)

Arguments

criteria

A valid model selection criteria for the collection of models. Includes loglik, BIC (all), ICL (PLNPCA) and pen_loglik, EBIC (PLNnetwork)

reverse

A logical indicating whether to plot the value of the criteria in the "natural" direction (loglik - 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 object


Method show()

User friendly print method

Usage

PLNfamily$show()


Method print()

User friendly print method

Usage

PLNfamily$print()


Method clone()

The objects of this class are cloneable with this method.

Usage

PLNfamily$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.