Asymptotic properties of mixture-of-experts models
Overview & Synopsis
The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the number of experts in the model. Our purpose is to extend the existing results for simple mixture models and mixtures of multilayer perceptrons. In this paper we first study a simple example which embodies all the difficulties arising in such models. We find that in the most general case the LRTS diverges but, with additional assumptions, the behavior of such models can be totally explicated.
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Document Information
| Document Title | Asymptotic properties of mixture-of-experts models |
|---|---|
| Author / Organization | Madalina Olteanu, Joseph Rynkiewicz |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2011 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-192406 |
| Original Source Link | Visit Source Page on hal.science » |