PLNmodels (version 1.2.2)

PLNfit_fixedcov: An R6 Class to represent a PLNfit in a standard, general framework, with fixed (inverse) residual covariance

Description

An R6 Class to represent a PLNfit in a standard, general framework, with fixed (inverse) residual covariance

An R6 Class to represent a PLNfit in a standard, general framework, with fixed (inverse) residual covariance

Super class

PLNmodels::PLNfit -> PLNfit_fixedcov

Active bindings

nb_param

number of parameters in the current PLN model

vcov_model

character: the model used for the residual covariance

vcov_coef

matrix of sandwich estimator of the variance-covariance of B (needs known covariance at the moment)

Methods

Public methods

• PLNfit_fixedcov$new()

• PLNfit_fixedcov$optimize()

• PLNfit_fixedcov$clone()

Inherited methods

• 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_fixedcov$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 optimize()

Call to the NLopt or TORCH optimizer and update of the relevant fields

Usage

PLNfit_fixedcov$optimize(responses, covariates, offsets, weights, config)

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.

config

part of the control argument which configures the optimizer

---

Method clone()

The objects of this class are cloneable with this method.

Usage

PLNfit_fixedcov$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

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