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On High-Dimensional Constrained Maximum Likelihood Inference
Inference in a high-dimensional situation may involve regularization of a certain form to treat overparameterization, imposing challenges to inference. The common practice of inference uses either a regularized model, as in inference after model selection, or bias-reduction known as “debias.” While...
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| Gepubliceerd in: | J Am Stat Assoc |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2019
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7418862/ https://ncbi.nlm.nih.gov/pubmed/32788818 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2018.1540986 |
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