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Reweighted madogram-type estimator of Pickands dependence function

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  • Zou, Nan

Abstract

This work proposes a reweighted, madogram-type estimator for the Pickands dependence function of bivariate time series and illustrates how it brings down the asymptotic bias and the overall mean squared error.

Suggested Citation

  • Zou, Nan, 2023. "Reweighted madogram-type estimator of Pickands dependence function," Statistics & Probability Letters, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:stapro:v:195:y:2023:i:c:s0167715223000147
    DOI: 10.1016/j.spl.2023.109790
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    References listed on IDEAS

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    1. Marcon, Giulia & Padoan, Simone & Naveau, Philippe & Muliere, Pietro & Segers, Johan, 2017. "Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials," LIDAM Reprints ISBA 2017003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Bucher, Axel & Segers, Johan, 2014. "Extreme value copula estimation based on block maxima of a multivariate stationary time series," LIDAM Reprints ISBA 2014019, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Philippe Naveau & Armelle Guillou & Daniel Cooley & Jean Diebolt, 2009. "Modelling pairwise dependence of maxima in space," Biometrika, Biometrika Trust, vol. 96(1), pages 1-17.
    4. Segers, Johan, 2012. "Nonparametric Inference for Max-Stable Dependence," LIDAM Reprints ISBA 2012007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Gudendorf, Gordon & Segers, Johan, 2012. "Nonparametric estimation of multivariate extreme-value copulas," LIDAM Reprints ISBA 2012011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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