simulate_new_somas: Simulation of new somas

In ComputationalIntelligenceGroup/3DSomaMS: 3DSomaMS: A univocal definition of the neuronal soma morphology using Gaussian mixture models

Description

Simulation of new somas of the clustering of bayesian networks

Usage

simulate_new_somas(model, data, cluster_number = NULL,
  number_of_new_instances = 100, seed = 1)

Arguments

model	a bn.fit object from bnlearn package whose nodes are gaussians. It must be the result of the BN_clustering function
data	the same dataset used to compute the bayesian_structure
cluster_number	a number between 1 and the number of clusters of model. When it is NULL, new somas are generated from the priori distribution. When is a number between 1 and the number of clusters, simulate new somas from the selected cluster.
number_of_new_instances	a natural number denoting the number of new somas sampled from simulation
seed	a natural number used as seed during the sampling, by default it is 1

Value

new_somas a dataset similar to data with the simulated somas

ComputationalIntelligenceGroup/3DSomaMS documentation built on May 6, 2019, 12:49 p.m.