Evaluate variational lower bound to determine when to stop VB-EM iteration (convergence).

1 | ```
vbound(X, model, prior)
``` |

`X` |
D x N numeric vector or matrix of N observations (columns) and D variables (rows) |

`model` |
List containing model parameters (see |

`prior` |
numeric vector or matrix containing the hyperparameters for the prior distributions |

A continuous scalar indicating the lower bound (the higher the more converged)

X is expected to be D x N for N observations (columns) and D variables (rows)

Yue Li

Mo Chen (2012). Matlab code for Variational Bayesian Inference for Gaussian Mixture Model. http://www.mathworks.com/matlabcentral/fileexchange/35362-variational-bayesian-inference-for-gaussian-mixture-model

Bishop, C. M. (2006). Pattern recognition and machine learning. Springer, Information Science and Statistics. NY, USA. (p474-486)

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