An R6 Class to represent a PLNfit in a standard, general framework, with spherical residual covariance

An R6 Class to represent a PLNfit in a standard, general framework, with spherical residual covariance

An R6 Class to represent a PLNfit in a standard, general framework, with spherical residual covariance

Super class

PLNmodels::PLNfit -> PLNfit_spherical

Active bindings

nb_param

number of parameters in the current PLN model

vcov_model

character: the model used for the residual covariance

Methods

Public methods

• PLNfit_spherical$new()

• PLNfit_spherical$clone()

Inherited methods

• PLNmodels::PLNfit$optimize()
• PLNmodels::PLNfit$optimize_vestep()
• PLNmodels::PLNfit$postTreatment()
• PLNmodels::PLNfit$predict()
• PLNmodels::PLNfit$predict_cond()
• PLNmodels::PLNfit$print()
• PLNmodels::PLNfit$show()
• PLNmodels::PLNfit$update()

---

Method new()

Initialize a PLNfit model

Usage

PLNfit_spherical$new(responses, covariates, offsets, weights, formula, control)

Arguments

responses

the matrix of responses (called Y in the model). Will usually be extracted from the corresponding field in PLNfamily-class

covariates

design matrix (called X in the model). Will usually be extracted from the corresponding field in PLNfamily-class

offsets

offset matrix (called O in the model). Will usually be extracted from the corresponding field in PLNfamily-class

weights

an optional vector of observation weights to be used in the fitting process.

formula

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

control

a list for controlling the optimization. See details.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PLNfit_spherical$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (FALSE) { # \dontrun{
data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
myPLN <- PLN(Abundance ~ 1, data = trichoptera)
class(myPLN)
print(myPLN)
} # }