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Fast inference in generalized linear models via expected log-likelihoods
Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can greatly facilitate computation. The basic idea is to replace a sum that appears in the exact log-likelihood by an expectati...
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| Pubblicato in: | J Comput Neurosci |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2013
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4374573/ https://ncbi.nlm.nih.gov/pubmed/23832289 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10827-013-0466-4 |
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