networkSamplingDyads_fit function

Virtual class used to define a family of networkSamplingDyads_fit

Virtual class used to define a family of networkSamplingDyads_fit

Virtual class used to define a family of networkSamplingDyads_fit

Super class

missSBM::networkSampling -> networkSamplingDyads_fit

Active bindings

• penalty: double, value of the penalty term in ICL

• log_lambda: double, term for adjusting the imputation step which depends on the type of sampling

Methods

Public methods

• list("networkSamplingDyads_fit$new()")

• list("networkSamplingDyads_fit$show()")

• list("networkSamplingDyads_fit$update_parameters()")

• list("networkSamplingDyads_fit$update_imputation()")

• list("networkSamplingDyads_fit$clone()")

Method new()

constructor for networkSampling_fit

Usage

networkSamplingDyads_fit$new(partlyObservedNetwork, name)

Arguments

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

• name: a character for the name of sampling to fit on the partlyObservedNetwork

Method show()

show method

Usage

networkSamplingDyads_fit$show()

Method update_parameters()

a method to update the estimation of the parameters. By default, nothing to do (corresponds to MAR sampling)

Usage

networkSamplingDyads_fit$update_parameters(...)

Arguments

• ...: use for compatibility

Method update_imputation()

a method to update the imputation of the missing entries.

Usage

networkSamplingDyads_fit$update_imputation(nu)

Arguments

• nu: the matrix of (uncorrected) imputation for missing entries

Method clone()

The objects of this class are cloneable with this method.

Usage

networkSamplingDyads_fit$clone(deep = FALSE)

Arguments

• deep: Whether to make a deep clone.