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Nonparametric Resampling for Homogeneous Strong Mixing Random Fields

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  • Politis, D. N.
  • Romano, J. P.

Abstract

Künsch (1989, Ann. Statist.17 1217-1241) and Liu ane Singh (1992, in Exploring Limits of Bootstrap (R. Le Page and L. Billard, Eds.), pp. 225-248, Wiley, New York) have recently introduced a block resampling method that is successful in deriving consistent bootstrap estimates of distribution and variance for the sample mean of a strong mixing sequence. Raïs and Moore (1990, in Interface '90) and Raïs (1992, Ph.D. Thesis, University of Montreal) extended the results of Künsch and Liu and Singh in the case of the sample mean of a homogeneous strong mixing random field in two dimensions (n = 2). In this paper, the general case (n [set membership, variant] Z+) is considered, and a resampling technique for strong mixing random fields is formulated, which is an extension of the "blocks of blocks" resampling scheme for sequences in Politis and Romano (1992, Ann. Statist.20 (4) 1985-2007). The "blocks of blocks" method can be used to construct asymptotically correct confidence intervals for parameters of the whole (infinite-dimensional) joint distribution of the random field, for example, the spectral density at a point. A variation of the "blocks of blocks" resampling scheme that involves "wrapping" the data around on a torus will also be studied, in view of its property to yield an unbiased bootstrap distribution.

Suggested Citation

  • Politis, D. N. & Romano, J. P., 1993. "Nonparametric Resampling for Homogeneous Strong Mixing Random Fields," Journal of Multivariate Analysis, Elsevier, vol. 47(2), pages 301-328, November.
    • Handle: RePEc:eee:jmvana:v:47:y:1993:i:2:p:301-328
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    1. Iranpanah, N. & Mohammadzadeh, M. & Taylor, C.C., 2011. "A comparison of block and semi-parametric bootstrap methods for variance estimation in spatial statistics," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 578-587, January.
    2. Buhlmann, Peter & Kunsch, Hans R., 1999. "Block length selection in the bootstrap for time series," Computational Statistics & Data Analysis, Elsevier, vol. 31(3), pages 295-310, September.
    3. Xianyang Zhang & Bo Li & Xiaofeng Shao, 2014. "Self-normalization for Spatial Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 311-324, June.
    4. Carbon, Michel & Tran, Lanh Tat & Wu, Berlin, 1997. "Kernel density estimation for random fields (density estimation for random fields)," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 115-125, December.
    5. Meyer, Marco & Jentsch, Carsten & Kreiss, Jens-Peter, 2015. "Baxter`s inequality and sieve bootstrap for random fields," Working Papers 15-06, University of Mannheim, Department of Economics.
    6. Bucchia, Béatrice & Wendler, Martin, 2017. "Change-point detection and bootstrap for Hilbert space valued random fields," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 344-368.
    7. Jeremy T. Fox & Patrick Bajari, 2013. "Measuring the Efficiency of an FCC Spectrum Auction," American Economic Journal: Microeconomics, American Economic Association, vol. 5(1), pages 100-146, February.
    8. Qihui Chen & Zheng Fang, 2018. "Improved Inference on the Rank of a Matrix," Papers 1812.02337, arXiv.org, revised Mar 2019.
    9. Michel Carbon, 2008. "Asymptotic Normality of Frequency Polygons for Random Fields," Working Papers 2008-09, Center for Research in Economics and Statistics.
    10. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Srijan Sengupta & Xiaofeng Shao & Yingchuan Wang, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 315-326, May.
    11. Raghu Nandan Sengupta & Rachit Seth & Peter Winker, 2023. "Reliability in Portfolio Optimization using Uncertain Estimates," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 199-233, May.
    12. Peter Buhlmann, 2007. "Bootstrap schemes for time series (in Russian)," Quantile, Quantile, issue 3, pages 37-56, September.
    13. Michel Carbon, 2014. "Histograms for stationary linear random fields," Statistical Inference for Stochastic Processes, Springer, vol. 17(3), pages 245-266, October.
    14. Michel Carbon, 2005. "Frequency Polygons for Random Fields," Working Papers 2005-04, Center for Research in Economics and Statistics.

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