Variational Bayes for generalized autoregressive models
We describe a variational Bayes (VB) learning algorithm for generalized autoregressive (GAR) models. The noise is modeled as a mixture of Gaussians rather than the usual single Gaussian. This allows different data points to be associated with different noise levels and effectively provides robust es...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2002
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