Posterior consistency in linear models under shrinkage priors
We investigate the asymptotic behaviour of posterior distributions of regression coefficients in highdimensional linear models as the number of dimensions grows with the number of observations. We show that the posterior distribution concentrates in neighbourhoods of the true parameter under simple...
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| Veröffentlicht in: | Biometrika 2013-12, Vol.100 (4), p.1011-1018 |
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| container_issue | 4 |
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| container_title | Biometrika |
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| creator | ARMAGAN, A. DUNSON, D. B. LEE, J. BAJWA, W. U. STRAWN, N. |
| description | We investigate the asymptotic behaviour of posterior distributions of regression coefficients in highdimensional linear models as the number of dimensions grows with the number of observations. We show that the posterior distribution concentrates in neighbourhoods of the true parameter under simple sufficient conditions. These conditions hold under popular shrinkage priors given some sparsity assumptions. |
| doi_str_mv | 10.1093/biomet/ast028 |
| format | Article |
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| ispartof | Biometrika, 2013-12, Vol.100 (4), p.1011-1018 |
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| language | eng |
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| source | Jstor Complete Legacy; Oxford Journals - Connect here FIRST to enable access; Alma/SFX Local Collection; JSTOR Mathematics & Business |
| subjects | Asymptotic methods Mathematical models Miscellanea Probability distribution Regression analysis Shrinkage Studies |
| title | Posterior consistency in linear models under shrinkage priors |
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