vbound {TargetScore} | R Documentation |
Evaluate variational lower bound to determine when to stop VB-EM iteration (convergence).
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)
X <- c(rnorm(100,mean=2), rnorm(100,mean=3)) tmp <- vbgmm(X, tol=1e-3) head(tmp$L) # lower bound should be strictly increasing