Submitted for publication:

  1. Bücher, A., Dette, H. and Heinrichs, F. (2020+): Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators: arxiv:2002.06143
  2. Bücher, A., El Ghouch, A. and Van Keilegom, I. (2015): Single-index quantile regression models for censored data.

Peer-reviewed journals:

  1. Bücher, A. and Jennessen T. (2020+): Method of moments estimators for the extremal index of a stationary time series. Erscheint in: Electronic Journal Of Statistics.
  2. Bücher, A. and Zhou, C. (2020+): A horse racing between the block maxima method and the peak-over-threshold approach. To appear in: Statistical Science.
  3. Bücher, A., Fried, R., Kinsvater, P. and Lilienthal, J. (2020+): Penalized Quasi-Maximum-Likelihood Estimation for Extreme Value Models with Application to Flood Frequency Analysis. To appear in: Extremes.
  4. Bücher, A., Posch, P. N. and Schmidtke, P. (2020+): Using the Extremal Index for Value-at-Risk Backtesting. To appear in: Journal of Financial Econometrics.
  5. Bücher, A., Volgushev, S. and Zou, N. (2020+): Multiple block sizes and overlapping blocks for multivariate time series extremes. To appear in: Annals of Statistics.
  6. Bücher, A., Dette, H. and Heinrichs, F. (2020): Detecting deviations from second-order stationarity in locally stationary functional time series. Annals of the Institute of Statistical Mathematics, Vol. 72(4), 1055-1094.
  7. Bücher, A., Volgushev, S. and Zou, N. (2019): On second order conditions in the multivariate block maxima and peak over threshold method. Journal of Multivariate Analysis, Vol. 173, 604-619.
  8. Bücher, A., Fermanian, J.-D. and Kojadinovic, I. (2019): Combining cumulative sum change-point detection tests for assessing the stationarity of univariate time series. Journal of Time Series Analysis 40: 124-150.
  9. Bücher, A. and Kojadinovic, I. (2019): A note on conditional versus joint unconditional weak convergence in bootstrap consistency results. Journal of Theoretical Probability, Vol. 32(3), 1145-1165.
  10. Berghaus, B. and Bücher, A. (2018): Weak Convergence of a Pseudo Maximum
    Likelihood Estimator for the Extremal Index. Annals of Statistics, Vol. 46(5), 2307-2335.
  11. Bücher, A. and Segers, J. (2018): On the maximum likelihood estimator for the
    Generalized Extreme-Value distribution. Extremes, Vol. 20(4), 839–872.
  12. Bücher, A. and Segers, J. (2018): Inference for heavy tailed stationary time series based
    on sliding blocks. Electronic Journal of Statistics, Vol. 12(1), 1098–1125.
  13. Bücher, A. and Segers, J. (2018): Maximum likelihood estimation for the Fréchet
    distribution based on block maxima extracted from a time series. Bernoulli Vol. 24(2), 1427–
    1462.
  14. Bücher, A., Irresberger, F. and Weiß, G. (2017): Testing Asymmetry in Dependence
    with Copula-Coskewness. North American Actuarial Journal, Vol. 21, 267–280.
  15. Bücher, A., Kinsvater, P. and Kojadinovic, I. (2017): Detecting breaks in the
    dependence of multivariate extreme-value distributions. Extremes, Vol. 20(1), 53-89.
  16. Berghaus, B. and Bücher, A. (2017): Goodness-of-fit tests for multivariate copula-based
    time series models. Econometric Theory, Vol. 33(2), 292–330.
  17. Berghaus, B., Bücher, A. and Volgushev, S. (2017): Weak convergence of the
    empirical copula process with respect to weighted metrics. Bernoulli, Vol. 23(1), 743–772.
  18. Bücher, A., Hoffmann, M., Vetter, M. and Dette, H. (2017): Nonparametric tests for
    detecting breaks in the jump behaviour of a time-continuous process. Bernoulli, Vol. 23(2), 1335–1364.
  19. Bücher, A. and Kojadinovic, I. (2016): A dependent multiplier bootstrap for the
    sequential empirical copula process under strong mixing. Bernoulli, Vol. 22(2), 927–968.
  20. Bücher, A., Jaschke, S. and Wied, D. (2015): Nonparametric tests for constant tail
    dependence with an application to energy and finance. Journal of Econometrics, Vol. 187(1), 154–168.
  21. Bücher, A. (2015): A note on weak convergence of the sequential multivariate empirical
    process under strong mixing. Journal of Theoretical Probability, Vol. 28(3), 1028–1037.
  22. Bücher, A. and Kojadinovic, I. (2015): Dependent multiplier bootstraps for nondegenerate
    U-statistics under mixing conditions with applications. Journal of Statistical Planning
    and Inference
    , Vol. 170, 83–105.
  23. Bücher, A., Segers, J. and Volgushev, S. (2014): When uniform weak convergence
    fails: empirical processes for dependence functions and residuals via epi- and hypographs.
    Annals of Statistics, Vol. 42, 1598–1634.
  24. Bücher, A. and Segers, J. (2014): Extreme value copula estimation based on block
    maxima of a multivariate stationary time series. Extremes, Vol. 13, 495–528.
  25. Bücher, A. (2014): A note on nonparametric estimation of bivariate tail dependence.
    Statistics & Risk Modeling, Vol. 31, 151–162.
  26. Bücher, A., Kojadinovic, I., Rohmer, T. and Segers, J. (2014): Detecting changes in
    cross-sectional dependence in multivariate time series. Journal of Multivariate Analysis, Vol. 132, 111–128.
  27. Berghaus, B. and Bücher, A. (2014): Nonparametric tests for tail monotonicity. Journal of
    Econometrics
    , Vol. 180(2), 117–126.
  28. Bücher, A. and Vetter, M. (2013): Nonparametric Inference on Lévy measures and
    copulas. Annals of Statistics, Vol. 41, 1485–1515.
  29. Bücher, A. and Dette, H. (2013): Multiplier bootstrap of tail copulas – with applications.
    Bernoulli, Vol. 5(A), 1655–1687.
  30. Bücher, A. and Ruppert, M. (2013): Consistent testing for a constant copula under strong
    mixing based on the tapered block multiplier technique. Journal of Multivariate Analysis, Vol. 116, 208–229.
  31. Bücher, A. and Volgushev, S. (2013): Empirical and sequential empirical copula
    processes under serial dependence. Journal of Multivariate Analysis, Vol. 119, 61–70.
  32. Berghaus, B., Bücher, A. and Dette H. (2013): Minimum distance estimators of the
    Pickands dependence function and related tests of multivariate extreme-value dependence.
    Journal de la Societé Francaise de Statistique, Vol. 154, 116– 137.
  33. Bücher, A., Dette, H. and Volgushev, S. (2012): A test for Archimedeanity in bivariate
    copula models. Journal of Multivariate Analysis, Vol. 110, 121–132.
  34. Bücher, A., Dette, H. and Volgushev, S. (2011): New estimators of the Pickands
    dependence function and a test for extreme-value dependence. Annals of Statistics, Vol. 39, No. 4, 1963–2006.
  35. Bücher, A., Dette, H. and Wieczorek, G. (2011): Testing model assumptions in
    functional regression models. Journal of Multivariate Analysis, Vol. 102, 1472– 1488.
  36. Bücher, A. and Dette, H. (2010): A note on bootstrap approximations for the empirical
    copula process. Statistics and Probability Letters, Vol. 80, 1925–1932.
  37. Bücher, A. and Dette, H. (2010): Some comments on goodness-of-fit tests for the
    parametric form of the copula based on L2-distances. Journal of Multivariate Analysis, Vol. 101, 749–763.

 Peer-reviewed book chapters:

  1. Bücher, A. and Kojadinovic, I. (2015): An overview of nonparametric tests of extremevalue dependence. In: Dey, D. and Yan, J: Extreme Value Modeling and Risk Analysis: Methods and Applications. Crc Press Inc, 2015, pages 377–398.

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