covarDyadSampling_fit: Class for fitting a dyad sampling with covariates

In jchiquet/missSBM: Handling Missing Data in Stochastic Block Models

Class for fitting a dyad sampling with covariates

Description

Class for fitting a dyad sampling with covariates

Class for fitting a dyad sampling with covariates

Super classes

missSBM::networkSampling -> missSBM::networkSamplingDyads_fit -> covarDyadSampling_fit

Active bindings

vExpec

variational expectation of the sampling

Methods

Public methods

• covarDyadSampling_fit$new()

• covarDyadSampling_fit$clone()

Inherited methods

• missSBM::networkSampling$print()
• missSBM::networkSamplingDyads_fit$show()
• missSBM::networkSamplingDyads_fit$update_imputation()
• missSBM::networkSamplingDyads_fit$update_parameters()

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Method new()

constructor

Usage

covarDyadSampling_fit$new(partialNet, ...)

Arguments

partialNet

a object with class partlyObservedNetwork representing the observed data with possibly missing entries

...

used for compatibility

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Method clone()

The objects of this class are cloneable with this method.

Usage

covarDyadSampling_fit$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

jchiquet/missSBM documentation built on Oct. 25, 2023, 5:30 a.m.