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Linear Model Selection when Covariates Contain Errors
Prediction precision is arguably the most relevant criterion of a model in practice and is often a sought after property. A common difficulty with covariates measured with errors is the impossibility of performing prediction evaluation on the data even if a model is completely given without any unkn...
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| Publicado no: | J Am Stat Assoc |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5798903/ https://ncbi.nlm.nih.gov/pubmed/29416191 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2016.1219262 |
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