Power of edge exclusion tests in graphical Gaussian models
Power of edge exclusion tests in graphical Gaussian models
Asymptotic multivariate normal approximations to the joint distributions of edge exclusion test statistics for saturated graphical Gaussian models are derived. Non-signed and signed square-root versions of the likelihood ratio, Wald and score test statistics are considered.
Noncentral chi-squared approximations are also considered for the non-signed versions. These approximations are used to estimate the power of edge exclusion tests and an example is presented.
likelihood ratio test, overall power, partial correlation, score test, signed square-root test, wald test
173-182
Salgueiro, M. Fátima
79450d95-f7a3-4695-9aa0-b2b18c4dc3ac
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
2005
Salgueiro, M. Fátima
79450d95-f7a3-4695-9aa0-b2b18c4dc3ac
Smith, Peter W.F.
961a01a3-bf4c-43ca-9599-5be4fd5d3940
McDonald, John W.
9adae16e-e1e1-4ddf-bf4c-7231ee8c1c8e
Salgueiro, M. Fátima, Smith, Peter W.F. and McDonald, John W.
(2005)
Power of edge exclusion tests in graphical Gaussian models.
Biometrika, 92 (1), .
(doi:10.1093/biomet/92.1.173).
Abstract
Asymptotic multivariate normal approximations to the joint distributions of edge exclusion test statistics for saturated graphical Gaussian models are derived. Non-signed and signed square-root versions of the likelihood ratio, Wald and score test statistics are considered.
Noncentral chi-squared approximations are also considered for the non-signed versions. These approximations are used to estimate the power of edge exclusion tests and an example is presented.
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Published date: 2005
Keywords:
likelihood ratio test, overall power, partial correlation, score test, signed square-root test, wald test
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Local EPrints ID: 40573
URI: http://eprints.soton.ac.uk/id/eprint/40573
ISSN: 0006-3444
PURE UUID: a2c66e28-960c-4348-9fe3-a2e56b915ee4
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Date deposited: 06 Jul 2006
Last modified: 16 Mar 2024 02:42
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Author:
M. Fátima Salgueiro
Author:
John W. McDonald
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