UpdateMix {vabayelMix}R Documentation

Internal function for: Variational Bayesian Gaussian Mixture Model

Description

Updates mean and variance parameters of mixture model.

Usage

UpdateMix(Ncat, data, m0, am0, aiv0, biv0, api0, m, am, aiv, biv, lambda, s.lambda)

Arguments

m0,am0,aiv0,biv0,api0 Prior hyperparameters, see vabayelMix
m,am,aiv,biv Posterior parameters.
lambda Categorical weight matrix, see References.
s.lambda Derived from lambda, see References.

Value

A list with the following components:

mean Means of gaussian posterior. Matrix of dimension Ncat x Ndim.
ivarm Inverse variances of gaussian posterior. Matrix of dimension Ncat x Ndim.
ivara,ivarb Parameters of gamma posterior. Matrices of dimension Ncat x Ndim.
dapi Parameters of dirichlet posterior giving weights of components.

Author(s)

Andrew Teschendorffaet21@hutchison-mrc.cam.ac.uk

References

1
D.J.MacKay: Developments in probabilistic modelling with neural networks-ensemble learning. In Neural Networks: Artificial Intelligence and Industrial Applications. Proceedings of the 3rd Annual Symposium on Neural Networksm Nijmengen, Netherlands, Berlin Springer, 191-198 (1995).
2
J. W. Miskin : Ensemble Learning for Independent Component Analysis, PhD thesis University of Cambridge December 2000.
3
A. E. Teschendorff,...et al.: A variational bayesian mixture modelling framework for cluster analysis of gene expression data. Submitted to Bioinformatics.


[Package vabayelMix version 0.3 Index]