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Manuscript.pdf

1903.09741.pdf
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🔗 Source: arxiv.org
📊 Size: 658 KB
📄 Pages: 48 pages
⬇️ Downloads: 111

Summary

The model assumes that the variations of covariates can be explained by a factor structure, with common factors and idiosyncratic components. The authors generalize the traditional sparsity assumption to assume that all common factors but only a small number of idiosyncratic components contribute to the response. A Bayesian procedure with a spike-and-slab prior is proposed for parameter estimation and model selection. Simulation studies and numerical results on a real dataset show that the Bayesian method outperforms its lasso analogue and is insensitive to overestimates of the number of common factors.

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Description

The model assumes that the variations of covariates can be explained by a factor structure, with common factors and idiosyncratic components.

Technical Information

  • File Format: PDF
  • File Size: 658 KB
  • Pages: 48
  • Language: EN
  • Total Downloads: 111
  • Last Updated: 3 hours ago

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