@article{BaringhausGaigall2015, author = {Baringhaus, Ludwig and Gaigall, Daniel}, title = {On an independence test approach to the goodness-of-fit problem}, series = {Journal of Multivariate Analysis}, volume = {2015}, journal = {Journal of Multivariate Analysis}, number = {140}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0047-259X}, doi = {10.1016/j.jmva.2015.05.013}, pages = {193 -- 208}, year = {2015}, abstract = {Let X₁,…,Xₙ be independent and identically distributed random variables with distribution F. Assuming that there are measurable functions f:R²→R and g:R²→R characterizing a family F of distributions on the Borel sets of R in the way that the random variables f(X₁,X₂),g(X₁,X₂) are independent, if and only if F∈F, we propose to treat the testing problem H:F∈F,K:F∉F by applying a consistent nonparametric independence test to the bivariate sample variables (f(Xᵢ,Xⱼ),g(Xᵢ,Xⱼ)),1⩽i,j⩽n,i≠j. A parametric bootstrap procedure needed to get critical values is shown to work. The consistency of the test is discussed. The power performance of the procedure is compared with that of the classical tests of Kolmogorov-Smirnov and Cram{\´e}r-von Mises in the special cases where F is the family of gamma distributions or the family of inverse Gaussian distributions.}, language = {en} } @phdthesis{Gaigall2016, author = {Gaigall, Daniel}, title = {Vergleich von statistischen Tests im verbundenen und unabh{\"a}ngigen Stichprobenfall}, publisher = {Gottfried Wilhelm Leibniz Universit{\"a}t Hannover}, address = {Hannover}, doi = {10.15488/8678}, pages = {281 Seiten}, year = {2016}, abstract = {Es werden Effizienzbegriffe zum Vergleich von statistischen Tests basierend auf verschiedenen statistischen Experimenten eingef{\"u}hrt. Dabei handelt es sich um die schon aus dem Vergleich von statistischen Tests in je demselben Modell bekannten asymptotischen relativen Effizienzen wie die Hodges-Lehmann-Effizienz, die Bahadur-Effizienz und die Pitman-Effizienz sowie um Kriterien basierend auf Volumina von Konfidenzbereichen. Effizienzaussagen werden unter anderem f{\"u}r Likelihood-Quotienten-Tests und Waldsche Tests im Rahmen eines allgemeinen multivariaten parametrischen Modells erhalten. Statistische Tests zur Pr{\"u}fung von Hypothesen {\"u}ber die relative Wirksamkeit zweier Experimente werden vorgeschlagen. Auf der Grundlage der erhaltenen Ergebnisse erfolgt ein Vergleich der Wirksamkeit von korrespondierenden Verfahren bei verbundener Stichprobenerhebung und unabh{\"a}ngiger Stichprobenerhebung. Die Rolle der Kovarianzmatrix bei verbundener Stichprobenerhebung wird insbesondere unter der Annahme, dass die zugrunde liegenden Verteilungen durch k-parametrische Exponentialfamilien modellierbar sind, herausgearbeitet. Verbindungen zu Effizienzbegriffen bei Punkt- und Konfidenzbereichssch{\"a}tzverfahren werden aufgezeigt. Ausf{\"u}hrlichere Untersuchungen betreffen die korrespondierenden Hotellingschen T²-Tests im multivariaten Normalverteilungsfall, die klassischen Homogenitatstests bei k × k-Kontingenztafeln und die Wilcoxon Tests in nichtparametrischen Lagealternativmodellen}, language = {de} } @article{BaringhausGaigall2017, author = {Baringhaus, Ludwig and Gaigall, Daniel}, title = {On Hotelling's T² test in a special paired sample case}, series = {Communications in Statistics - Theory and Methods}, volume = {48}, journal = {Communications in Statistics - Theory and Methods}, number = {2}, publisher = {Taylor \& Francis}, address = {London}, issn = {1532-415X}, doi = {10.1080/03610926.2017.1408828}, pages = {257 -- 267}, year = {2017}, abstract = {In a special paired sample case, Hotelling's T² test based on the differences of the paired random vectors is the likelihood ratio test for testing the hypothesis that the paired random vectors have the same mean; with respect to a special group of affine linear transformations it is the uniformly most powerful invariant test for the general alternative of a difference in mean. We present an elementary straightforward proof of this result. The likelihood ratio test for testing the hypothesis that the covariance structure is of the assumed special form is derived and discussed. Applications to real data are given.}, 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{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{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{BaringhausGaigallThiele2018, author = {Baringhaus, Ludwig and Gaigall, Daniel and Thiele, Jan Philipp}, title = {Statistical inference for L²-distances to uniformity}, series = {Computational Statistics}, volume = {2018}, journal = {Computational Statistics}, number = {33}, publisher = {Springer}, address = {Berlin}, issn = {1613-9658}, doi = {10.1007/s00180-018-0820-0}, pages = {1863 -- 1896}, year = {2018}, abstract = {The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L²-distances to uniformity based on the empirical distribution function, the integrated empirical distribution function and the integrated empirical survival function. Approximations of power functions, confidence intervals for the L²-distances and statistical neighbourhood-of-uniformity validation tests are obtained as main applications. The finite sample behaviour of the procedures is illustrated by a simulation study.}, 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} } @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{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} }