BIC_criterion: Bayesian Information Criterion

In QuantumClone: Clustering Mutations using High Throughput Sequencing (HTS) Data

Description

Computes BIC from a list of outputs of EM algorithm, then returns the position with minimal BIC

Usage

BIC_criterion(EM_out_list, model.selection)

Arguments

EM_out_list	list of outputs from EM.algo or FullEM
model.selection	The function to minimize for the model selection: can be "AIC", "BIC", or numeric. In numeric, the BIC function is modified. If variance: returns max(abs(1 - Var(cluster)/expected(Var)))

QuantumClone documentation built on May 2, 2019, 3:03 a.m.