1977
DOI: 10.2307/2335787
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A Ridge-Type Procedure for Design of Experiments

Abstract: JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Biometrika Trust is collaborating with JSTOR to digitize, preserve and extend access to Biometrika. Miscellanea 147When the centre point is somewhat more heavily weighted than… Show more

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Cited by 19 publications
(4 citation statements)
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“…The posterior mean b = b(r) is interpreted as a Bayesian shrinkage estimator of the coefficients or merely as a ridge regression estimator. See Efron and Morris (1973), Oman (1984), and Vuchkov (1977) for discussion of such estimators. One can examine the ridge trace-namely, b(r) as r varies-to evaluate the sensitivity of the parameter estimates to the prior distribution.…”
Section: Analysis Strategymentioning
confidence: 99%
“…The posterior mean b = b(r) is interpreted as a Bayesian shrinkage estimator of the coefficients or merely as a ridge regression estimator. See Efron and Morris (1973), Oman (1984), and Vuchkov (1977) for discussion of such estimators. One can examine the ridge trace-namely, b(r) as r varies-to evaluate the sensitivity of the parameter estimates to the prior distribution.…”
Section: Analysis Strategymentioning
confidence: 99%
“…Except for the simple or the weighted random choice of a saturated set S ⊆ F, the most common is the procedure based on a regularization of the information matrix of a sub-saturated set (see, e.g., Section 11.2 of [2]; cf. [31]). The regularized greedy heuristic (RGH) specifies step (S) as…”
Section: The Regularized Greedy Heuristic (Rgh)mentioning
confidence: 99%
“…As far as we know, the first discussion of regularized ODOE comes from Vuchkov (1977), who proposed a ridge-type procedure for ODOE based on the ridge regression estimator: βridge = argmin…”
Section: Regularized Odoe On Manifoldsmentioning
confidence: 99%