@article{DitzhausGaigall2018,
  author    = {Ditzhaus, Marc and Gaigall, Daniel},
  title     = {A consistent goodness-of-fit test for huge dimensional and functional data},
  series = {Journal of Nonparametric Statistics},
  volume    = {30},
  journal   = {Journal of Nonparametric Statistics},
  number    = {4},
  publisher = {Taylor \& Francis},
  address   = {Abingdon},
  issn      = {1029-0311},
  doi       = {10.1080/10485252.2018.1486402},
  pages     = {834 -- 859},
  year      = {2018},
  abstract  = {A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cram{\´e}r-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals.},
  language  = {en}
}
@article{BaringhausGaigall2022,
  author    = {Baringhaus, Ludwig and Gaigall, Daniel},
  title     = {A goodness-of-fit test for the compound Poisson exponential model},
  series = {Journal of Multivariate Analysis},
  volume    = {195},
  journal   = {Journal of Multivariate Analysis},
  number    = {Article 105154},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0047-259X},
  doi       = {10.1016/j.jmva.2022.105154},
  year      = {2022},
  abstract  = {On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed.},
  language  = {en}
}
@article{Gaigall2023,
  author    = {Gaigall, Daniel},
  title     = {Allocating and forecasting changes in risk},
  series = {Journal of risk},
  volume    = {25},
  journal   = {Journal of risk},
  number    = {3},
  editor    = {AitSahlia, Farid},
  publisher = {Infopro Digital Risk},
  address   = {London},
  issn      = {1755-2842},
  doi       = {10.21314/JOR.2022.048},
  pages     = {1 -- 24},
  year      = {2023},
  abstract  = {We consider time-dependent portfolios and discuss the allocation of changes in the risk of a portfolio to changes in the portfolio's components. For this purpose we adopt established allocation principles. We also use our approach to obtain forecasts for changes in the risk of the portfolio's components. To put the approach into practice we present an implementation based on the output of a simulation. Allocation is illustrated with an example portfolio in the context of Solvency II. The quality of the forecasts is investigated with an empirical study.},
  language  = {en}
}
@article{GaigallGerstenberg2023,
  author    = {Gaigall, Daniel and Gerstenberg, Julian},
  title     = {Cram{\´e}r-von-Mises tests for the distribution of the excess over a confidence level},
  series = {Journal of Nonparametric Statistics},
  journal   = {Journal of Nonparametric Statistics},
  publisher = {Taylor \& Francis},
  issn      = {1048-5252 (Print)},
  doi       = {10.1080/10485252.2023.2173958},
  year      = {2023},
  abstract  = {The Cram{\´e}r-von-Mises distance is applied to the distribution of the excess over a confidence level. Asymptotics of related statistics are investigated, and it is seen that the obtained limit distributions differ from the classical ones. For that reason, quantiles of the new limit distributions are given and new bootstrap techniques for approximation purposes are introduced and justified. The results motivate new one-sample goodness-of-fit tests for the distribution of the excess over a confidence level and a new confidence interval for the related fitting error. Simulation studies investigate size and power of the tests as well as coverage probabilities of the confidence interval in the finite sample case. A practice-oriented application of the Cram{\´e}r-von-Mises tests is the determination of an appropriate confidence level for the fitting approach. The adoption of the idea to the well-known problem of threshold detection in the context of peaks over threshold modelling is sketched and illustrated by data examples.},
  language  = {en}
}
@article{BaringhausGaigall2018,
  author    = {Baringhaus, Ludwig and Gaigall, Daniel},
  title     = {Efficiency comparison of the Wilcoxon tests in paired and independent survey samples},
  series = {Metrika},
  volume    = {2018},
  journal   = {Metrika},
  number    = {81},
  publisher = {Springer},
  address   = {Berlin},
  issn      = {1435-926X},
  doi       = {10.1007/s00184-018-0661-4},
  pages     = {891 -- 930},
  year      = {2018},
  abstract  = {The efficiency concepts of Bahadur and Pitman are used to compare the Wilcoxon tests in paired and independent survey samples. A comparison through the length of corresponding confidence intervals is also done. Simple conditions characterizing the dominance of a procedure are derived. Statistical tests for checking these conditions are suggested and discussed.},
  language  = {de}
}
@article{GaigallGerstenbergTrinh2022,
  author    = {Gaigall, Daniel and Gerstenberg, Julian and Trinh, Thi Thu Ha},
  title     = {Empirical process of concomitants for partly categorial data and applications in statistics},
  series = {Bernoulli},
  volume    = {28},
  journal   = {Bernoulli},
  number    = {2},
  publisher = {International Statistical Institute},
  address   = {Den Haag, NL},
  issn      = {1573-9759},
  doi       = {10.3150/21-BEJ1367},
  pages     = {803 -- 829},
  year      = {2022},
  abstract  = {On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings.},
  language  = {en}
}
@article{Gaigall2020,
  author    = {Gaigall, Daniel},
  title     = {Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic on partly not identically distributed data},
  series = {Communications in Statistics - Theory and Methods},
  volume    = {51},
  journal   = {Communications in Statistics - Theory and Methods},
  number    = {12},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1532-415X},
  doi       = {10.1080/03610926.2020.1805767},
  pages     = {4006 -- 4028},
  year      = {2020},
  abstract  = {The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.},
  language  = {en}
}
@article{BaringhausGaigall2017,
  author    = {Baringhaus, Ludwig and Gaigall, Daniel},
  title     = {Hotelling's T² tests in paired and independent survey samples: An efficiency comparison},
  series = {Journal of Multivariate Analysis},
  volume    = {2017},
  journal   = {Journal of Multivariate Analysis},
  number    = {154},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0047-259X},
  doi       = {10.1016/j.jmva.2016.11.004},
  pages     = {177 -- 198},
  year      = {2017},
  abstract  = {Hotelling's T² tests in paired and independent survey samples are compared using the traditional asymptotic efficiency concepts of Hodges-Lehmann, Bahadur and Pitman, as well as through criteria based on the volumes of corresponding confidence regions. Conditions characterizing the superiority of a procedure are given in terms of population canonical correlation type coefficients. Statistical tests for checking these conditions are developed. Test statistics based on the eigenvalues of a symmetrized sample cross-covariance matrix are suggested, as well as test statistics based on sample canonical correlation type coefficients.},
  language  = {en}
}
@article{Gaigall2019,
  author    = {Gaigall, Daniel},
  title     = {On a new approach to the multi-sample goodness-of-fit problem},
  series = {Communications in Statistics - Simulation and Computation},
  volume    = {53},
  journal   = {Communications in Statistics - Simulation and Computation},
  number    = {10},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1532-4141},
  doi       = {10.1080/03610918.2019.1618472},
  pages     = {2971 -- 2989},
  year      = {2019},
  abstract  = {Suppose we have k samples X₁,₁,…,X₁,ₙ₁,…,Xₖ,₁,…,Xₖ,ₙₖ with different sample sizes ₙ₁,…,ₙₖ and unknown underlying distribution functions F₁,…,Fₖ as observations plus k families of distribution functions {G₁(⋅,ϑ);ϑ∈Θ},…,{Gₖ(⋅,ϑ);ϑ∈Θ}, each indexed by elements ϑ from the same parameter set Θ, we consider the new goodness-of-fit problem whether or not (F₁,…,Fₖ) belongs to the parametric family {(G₁(⋅,ϑ),…,Gₖ(⋅,ϑ));ϑ∈Θ}. New test statistics are presented and a parametric bootstrap procedure for the approximation of the unknown null distributions is discussed. Under regularity assumptions, it is proved that the approximation works asymptotically, and the limiting distributions of the test statistics in the null hypothesis case are determined. Simulation studies investigate the quality of the new approach for small and moderate sample sizes. Applications to real-data sets illustrate how the idea can be used for verifying model assumptions.},
  language  = {en}
}
@article{BaringhausGaigall2019,
  author    = {Baringhaus, Ludwig and Gaigall, Daniel},
  title     = {On an asymptotic relative efficiency concept based on expected volumes of confidence regions},
  series = {Statistics - A Journal of Theoretical and Applied Statistic},
  volume    = {53},
  journal   = {Statistics - A Journal of Theoretical and Applied Statistic},
  number    = {6},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1029-4910},
  doi       = {10.1080/02331888.2019.1683560},
  pages     = {1396 -- 1436},
  year      = {2019},
  abstract  = {The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions associated with certain plugin estimators, likelihood ratio tests and Wald tests. Under regularity conditions, the asymptotic relative efficiency of each of these procedures with respect to each one of its competitors is equal to 1. The results are applied to multivariate normal distributions and multinomial distributions in a fairly general setting.},
  language  = {en}
}