# R: Smooth the path ICL in a collection of missSBM_fit models

smooth {missSBM} | R Documentation

## Smooth the path ICL in a collection of missSBM_fit models

### Description

Apply a split and/or merge strategy of the clustering in a path of models in a collection of SBM ordered by number of block. The goal is to find better initialization. This results in a "smoothing" of the ICL, that should be close to concave.

### Usage

    smooth(Robject, type = c("forward", "backward", "both"),
      control = list())

### Arguments

`Robject` | an object with class missSBM_collection, i.e. an output from `estimate`
`type` | character indicating what kind of ICL smoothing should be use among "forward", "backward" or "both". Default is "forward".
`control` | a list controlling the variational EM algorithm. See details.

### Details

The list of parameters `control` controls the optimization process and the variational EM algorithm, with the following entries

- "iterates"integer for the number of iteration of smoothing. Default is 1.

- "threshold"stop when an optimization step changes the objective function by less than threshold. Default is 1e-4.

- "maxIter"V-EM algorithm stops when the number of iteration exceeds maxIter. Default is 200

- "fixPointIter"number of fix-point iteration for the Variational E step. Default is 5.

- "cores"integer for number of cores used. Default is 1.

- "trace"integer for verbosity. Useless when `cores` > 1

### Value

an invisible missSBM_collection, in which the ICL has been smoothed

[Package missSBM version 0.2.0 Index]