# Variational Lower Bound Evaluation

### Description

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

### Usage

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

### Arguments

`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 |

### Value

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

### Note

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

### Author(s)

Yue Li

### References

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)

### See Also

`vbgmm`

### Examples

1 2 3 |