# Mstep: M-step In noisySBM: Noisy Stochastic Block Mode: Graph Inference by Multiple Testing

## Description

performs one M-step, that is, update of pi, w, nu, nu0

## Usage

 `1` ```Mstep(VE, mstep, model, data, modelFamily, directed) ```

## Arguments

 `VE` list with variational parameters tau and rho `mstep` list with current model parameters and additional auxiliary terms `model` Implemented models: `Gauss`all Gaussian parameters of the null and the alternative distributions are unknown ; this is the Gaussian model with maximum number of unknown parameters `Gauss0`compared to `Gauss`, the mean of the null distribution is set to 0 `Gauss01`compared to `Gauss`, the null distribution is set to N(0,1) `GaussEqVar`compared to `Gauss`, all Gaussian variances (of both the null and the alternative) are supposed to be equal, but unknown `Gauss0EqVar`compared to `GaussEqVar`, the mean of the null distribution is set to 0 `Gauss0Var1`compared to `Gauss`, all Gaussian variances are set to 1 and the null distribution is set to N(0,1) `Gauss2distr`the alternative distribution is a single Gaussian distribution, i.e. the block memberships of the nodes do not influence on the alternative distribution `GaussAffil`compared to `Gauss`, for the alternative distribution, there's a distribution for inter-group and another for intra-group interactions `Exp`the null and the alternatives are all exponential distributions (i.e. Gamma distributions with shape parameter equal to one) with unknown scale parameters `ExpGamma`the null distribution is an unknown exponential, the alterantive distribution are Gamma distributions with unknown parameters `data` data vector in the undirected model, data matrix in the directed model `modelFamily` probability distribution for the edges. Possible values: `Gauss`, `Gamma` `directed` booelan to indicate whether the model is directed or undirected

## Value

updated list `mstep` with current model parameters and additional auxiliary terms

noisySBM documentation built on Dec. 16, 2020, 5:09 p.m.