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A Composite Likelihood Cross‐validation Approach in Selecting Bandwidth for the Estimation of the Pair Correlation Function

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  • YONGTAO GUAN

Abstract

. A useful tool while analysing spatial point patterns is the pair correlation function (e.g. Fractals, Random Shapes and Point Fields, Wiley, New York, 1994). In practice, this function is often estimated by some nonparametric procedure such as kernel smoothing, where the smoothing parameter (i.e. bandwidth) is often determined arbitrarily. In this article, a data‐driven method for the selection of the bandwidth is proposed. The efficacy of the proposed approach is studied through both simulations and an application to a forest data example.

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  • Yongtao Guan, 2007. "A Composite Likelihood Cross‐validation Approach in Selecting Bandwidth for the Estimation of the Pair Correlation Function," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(2), pages 336-346, June.
    • Handle: RePEc:bla:scjsta:v:34:y:2007:i:2:p:336-346
    DOI: 10.1111/j.1467-9469.2006.00533.x
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    Cited by:

    1. Yasuhiro Saito & Tadashi Dohi & Won Y Yun, 2016. "Kernel-based nonparametric estimation methods for a periodic replacement problem with minimal repair," Journal of Risk and Reliability, , vol. 230(1), pages 54-66, February.
    2. Jha, Amit Prakash & Mahajan, Aarushi & Singh, Sanjay Kumar & Kumar, Piyush, 2022. "Renewable energy proliferation for sustainable development: Role of cross-border electricity trade," Renewable Energy, Elsevier, vol. 201(P1), pages 1189-1199.
    3. Ji Meng Loh & Woncheol Jang, 2010. "Estimating a cosmological mass bias parameter with bootstrap bandwidth selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 761-779, November.
    4. Jonatan A. González & Francisco J. Rodríguez-Cortés & Elvira Romano & Jorge Mateu, 2021. "Classification of Events Using Local Pair Correlation Functions for Spatial Point Patterns," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(4), pages 538-559, December.
    5. Ute Hahn & Eva B. Vedel Jensen, 2016. "Hidden Second-order Stationary Spatial Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 455-475, June.
    6. Isabel Fuentes-Santos & Wenceslao González-Manteiga & Jorge Mateu, 2016. "Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 416-435, June.
    7. Cristiano Varin, 2008. "On composite marginal likelihoods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 1-28, February.

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