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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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Dades bibliogràfiques
Publicat a:J Am Stat Assoc
Autors principals: Zhang, Xinyu, Wang, Haiying, Ma, Yanyuan, Carroll, Raymond J.
Format: Artigo
Idioma:Inglês
Publicat: 2017
Matèries:
Accés en línia: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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