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Power of edge exclusion tests in graphical Gaussian models

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  • M. Fátima Salgueiro
  • Peter W. F. Smith
  • John W. McDonald

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. Copyright 2005, Oxford University Press.

Suggested Citation

  • M. Fátima Salgueiro & Peter W. F. Smith & John W. McDonald, 2005. "Power of edge exclusion tests in graphical Gaussian models," Biometrika, Biometrika Trust, vol. 92(1), pages 173-182, March.
    • Handle: RePEc:oup:biomet:v:92:y:2005:i:1:p:173-182
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    File URL: http://hdl.handle.net/10.1093/biomet/92.1.173
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    Cited by:

    1. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    2. Christis Katsouris, 2023. "Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models," Papers 2305.11282, arXiv.org, revised Jul 2023.
    3. Maria Salgueiro & Peter Smith & John McDonald, 2008. "The Manifest Association Structure of the Single-Factor Model: Insights from Partial Correlations," Psychometrika, Springer;The Psychometric Society, vol. 73(4), pages 665-670, December.
    4. Fátima Salgueiro, M. & Smith, Peter W.F. & McDonald, John W., 2006. "Power of edge exclusion tests for graphical log-linear models," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1691-1701, September.

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