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Efficient pairwise composite likelihood estimation for spatial-clustered data

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  • Yun Bai
  • Jian Kang
  • Peter X.-K. Song

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  • Yun Bai & Jian Kang & Peter X.-K. Song, 2014. "Efficient pairwise composite likelihood estimation for spatial-clustered data," Biometrics, The International Biometric Society, vol. 70(3), pages 661-670, September.
    • Handle: RePEc:bla:biomet:v:70:y:2014:i:3:p:661-670
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    File URL: http://hdl.handle.net/10.1111/biom.12199
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Peter Diggle & Rana Moyeed & Barry Rowlingson & Madeleine Thomson, 2002. "Childhood malaria in the Gambia: a case‐study in model‐based geostatistics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(4), pages 493-506, October.
    3. Cristiano Varin, 2008. "On composite marginal likelihoods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 1-28, February.
    4. Yun Bai & Peter X.-K. Song & T. E. Raghunathan, 2012. "Joint composite estimating functions in spatiotemporal models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(5), pages 799-824, November.
    5. Peter Xue‐Kun Song, 2000. "Multivariate Dispersion Models Generated From Gaussian Copula," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(2), pages 305-320, June.
    6. Moreno Bevilacqua & Carlo Gaetan & Jorge Mateu & Emilio Porcu, 2012. "Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 268-280, March.
    7. Sener, Ipek N. & Pendyala, Ram M. & Bhat, Chandra R., 2011. "Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior," Journal of Transport Geography, Elsevier, vol. 19(2), pages 294-303.
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    Cited by:

    1. Frédéric Lavancier & Arnaud Poinas & Rasmus Waagepetersen, 2021. "Adaptive estimating function inference for nonstationary determinantal point processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 87-107, March.
    2. L. L. Henn, 2022. "Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data," Computational Statistics, Springer, vol. 37(2), pages 909-946, April.
    3. Moreno Bevilacqua & Christian Caamaño-Carrillo & Reinaldo B. Arellano-Valle & Camilo Gómez, 2022. "A class of random fields with two-piece marginal distributions for modeling point-referenced data with spatial outliers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 644-674, September.
    4. Moreno Bevilacqua & Christian Caamaño‐Carrillo & Reinaldo B. Arellano‐Valle & Víctor Morales‐Oñate, 2021. "Non‐Gaussian geostatistical modeling using (skew) t processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 212-245, March.
    5. Jiajie Kong & Robert Lund, 2023. "Seasonal count time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 93-124, January.
    6. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
    7. Kangning Wang & Mengjie Hao & Xiaofei Sun, 2021. "Robust and efficient estimating equations for longitudinal data partial linear models and its applications," Statistical Papers, Springer, vol. 62(5), pages 2147-2168, October.
    8. Andréas Heinen & James B. Kau & Donald C. Keenan & Mi Lim Kim, 2021. "Spatial Dependence in Subprime Mortgage Defaults," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 1-24, January.
    9. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
    10. Kangning Wang & Wen Shan, 2021. "Copula and composite quantile regression-based estimating equations for longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 441-455, June.
    11. Zifeng Zhao & Peng Shi & Xiaoping Feng, 2021. "Knowledge Learning of Insurance Risks Using Dependence Models," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1177-1196, July.
    12. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
    13. Shi Chen & Wolfgang Karl Härdle & Weining Wang, 2022. "The common and specific components of inflation expectations across European countries," Empirical Economics, Springer, vol. 62(2), pages 553-580, February.
    14. Victor De Oliveira, 2017. "Geostatistical Binary Data: Models, Properties And Connections," Working Papers 0151mss, College of Business, University of Texas at San Antonio.
    15. Xiaotian Zheng & Athanasios Kottas & Bruno Sansó, 2023. "Bayesian geostatistical modeling for discrete‐valued processes," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.

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