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Barnard's Monte Carlo Tests: How Many Simulations?

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  • F. H. C. Marriott

Abstract

The Monte Carlo test proposed by Barnard, often used in investigating spatial distributions, gives a “blurred” critical region, in which values of the test statistic have a certain probability of being judged significant. The effect of increasing the number of simulations on this blurring is investigated.

Suggested Citation

  • F. H. C. Marriott, 1979. "Barnard's Monte Carlo Tests: How Many Simulations?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(1), pages 75-77, March.
    • Handle: RePEc:bla:jorssc:v:28:y:1979:i:1:p:75-77
    DOI: 10.2307/2346816
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    Cited by:

    1. Kiviet, Jan F. & Dufour, Jean-Marie, 1997. "Exact tests in single equation autoregressive distributed lag models," Journal of Econometrics, Elsevier, vol. 80(2), pages 325-353, October.
    2. Pascale VALERY (HEC-Montreal) & Jean-Marie Dufour (University of Montreal), 2004. "A simple estimation method and finite-sample inference for a stochastic volatility model," Econometric Society 2004 North American Summer Meetings 153, Econometric Society.
    3. Davidson, Russell & MacKinnon, James G., 1996. "The Power of Bootstrap Tests," Queen's Institute for Economic Research Discussion Papers 273372, Queen's University - Department of Economics.
    4. Jouneau-Sion, Frederic & Torres, Olivier, 2006. "MMC techniques for limited dependent variables models: Implementation by the branch-and-bound algorithm," Journal of Econometrics, Elsevier, vol. 133(2), pages 479-512, August.
    5. Cees Diks & Valentyn Panchenko, 2005. "Nonparametric Tests for Serial Independence Based on Quadratic Forms," Tinbergen Institute Discussion Papers 05-076/1, Tinbergen Institute.
    6. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    7. S Raybould & M G Coombes, 1992. "The Research Potential of Administrative Data: An Illustrative Example of the Utility of Register Information in Spatial Analysis," Environment and Planning B, , vol. 19(2), pages 131-142, April.
    8. Diks, Cees, 2003. "Detecting serial dependence in tail events: a test dual to the BDS test," Economics Letters, Elsevier, vol. 79(3), pages 319-324, June.
    9. Diks Cees & Panchenko Valentyn, 2008. "Rank-based Entropy Tests for Serial Independence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-21, March.
    10. Chiu, Sung Nok & Wang, Ling, 2009. "Homogeneity tests for several Poisson populations," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4266-4278, October.
    11. Ugo Santosuosso & Alessio Papini, 2022. "An analysis about the accuracy of geographic profiling in relation to the number of observations and the buffer zone," Journal of Geographical Systems, Springer, vol. 24(4), pages 641-656, October.
    12. Russell Davidson & James MacKinnon, 2000. "Bootstrap tests: how many bootstraps?," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 55-68.
    13. Jesse Hemerik & Jelle J. Goeman & Livio Finos, 2020. "Robust testing in generalized linear models by sign flipping score contributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 841-864, July.
    14. Chiu, Sung Nok & Liu, Kwong Ip, 2009. "Generalized Cramér-von Mises goodness-of-fit tests for multivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3817-3834, September.
    15. Angus, J.E., 1984. "The connection between the Barnard-Birnbaum Monte Carlo test and the two-sample Kolmogorov-Smirnov test," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 26(1), pages 20-22.

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