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Graphical methods for investigating the finite-sample properties of confidence regions

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  • de Peretti, Christian
  • Siani, Carole

Abstract

No satisfactory method for measuring and presenting the performance of confidence regions can be found in the literature. Techniques for measuring the effectiveness of confidence regions and for the graphical display of simulation evidence regarding the coverage and effectiveness of confidence regions are developed and illustrated. Three types of figures are discussed: called coverage plots, coverage discrepancy plots, and coverage effectiveness curves, which makes it possible to show the "genuine" effectiveness, rather than a spurious nominal effectiveness. These figures are used to illustrate the finite sample properties of autoregressive parameter confidence regions in the context of AR(1) processes.

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  • de Peretti, Christian & Siani, Carole, 2010. "Graphical methods for investigating the finite-sample properties of confidence regions," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 262-271, February.
    • Handle: RePEc:eee:csdana:v:54:y:2010:i:2:p:262-271
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    1. Tang, Man-Lai & Tian, Maozai, 2009. "Asymptotic confidence interval construction for risk difference under inverse sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 621-631, January.
    2. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    3. Bruce E. Hansen, 1999. "The Grid Bootstrap And The Autoregressive Model," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 594-607, November.
    4. Miao, Weiwen & Chiou, Paul, 2008. "Confidence intervals for the difference between two means," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2238-2248, January.
    5. Xu, Jin & Gupta, Arjun K., 2006. "Improved confidence regions for a mean vector under general conditions," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1051-1062, November.
    6. Arteche, Josu & Orbe, Jesus, 2009. "Using the bootstrap for finite sample confidence intervals of the log periodogram regression," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1940-1953, April.
    7. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, vol. 15(3), pages 361-376, June.
    8. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
    9. Su, Steve, 2009. "Confidence intervals for quantiles using generalized lambda distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3324-3333, July.
    10. Gregory, Allan W & Veall, Michael R, 1985. "Formulating Wald Tests of Nonlinear Restrictions," Econometrica, Econometric Society, vol. 53(6), pages 1465-1468, November.
    11. Davidson, Russell & MacKinnon, James G., 2006. "The power of bootstrap and asymptotic tests," Journal of Econometrics, Elsevier, vol. 133(2), pages 421-441, August.
    12. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
    13. Lee, A. J. & Nyangoma, S. O. & Seber, G. A. F., 2002. "Confidence regions for multinomial parameters," Computational Statistics & Data Analysis, Elsevier, vol. 39(3), pages 329-342, May.
    14. Gonzalez, Juan R. & Peña, Edsel A. & Delicado, Pedro, 2010. "Confidence intervals for median survival time with recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 78-89, January.
    15. Wang, Hongkun & Zhao, Yichuan, 2009. "A comparison of some confidence intervals for the mean quality-adjusted lifetime with censored data," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2733-2739, May.
    16. Chung, Hie-Choon & Han, Chien-Pai, 2009. "Conditional confidence intervals for classification error rate," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4358-4369, October.
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    Cited by:

    1. Dashi I. Singham & Lee W. Schruben, 2012. "Finite-Sample Performance of Absolute Precision Stopping Rules," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 624-635, November.

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