PLNfamily | R Documentation |

super class for `PLNPCAfamily`

and `PLNnetworkfamily`

.

`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.

`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)

`new()`

Create a new `PLNfamily`

object.

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

`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

A new `PLNfamily`

object

`postTreatment()`

Update fields after optimization

PLNfamily$postTreatment(config_post, config_optim)

`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

`getModel()`

Extract a model from a collection of models

PLNfamily$getModel(var, index = NULL)

`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.

A `PLNfit`

object

`plot()`

Lineplot of selected criteria for all models in the collection

PLNfamily$plot(criteria, reverse)

`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.

A `ggplot2`

object

`show()`

User friendly print method

PLNfamily$show()

`print()`

User friendly print method

PLNfamily$print()

`clone()`

The objects of this class are cloneable with this method.

PLNfamily$clone(deep = FALSE)

`deep`

Whether to make a deep clone.

`getModel()`

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